Overview

Dataset statistics

Number of variables183
Number of observations1524579
Missing cells220469465
Missing cells (%)79.0%
Duplicate rows5
Duplicate rows (%)< 0.1%
Total size in memory2.1 GiB
Average record size in memory1.4 KiB

Variable types

NUM98
CAT61
UNSUPPORTED17
URL7

Warnings

Dataset has 5 (< 0.1%) duplicate rows Duplicates
creator has a high cardinality: 12355 distinct values High cardinality
created_datetime has a high cardinality: 1276844 distinct values High cardinality
last_modified_datetime has a high cardinality: 1164947 distinct values High cardinality
product_name has a high cardinality: 967856 distinct values High cardinality
generic_name has a high cardinality: 78579 distinct values High cardinality
quantity has a high cardinality: 33349 distinct values High cardinality
packaging has a high cardinality: 42038 distinct values High cardinality
packaging_tags has a high cardinality: 33985 distinct values High cardinality
packaging_text has a high cardinality: 471 distinct values High cardinality
brands has a high cardinality: 146872 distinct values High cardinality
brands_tags has a high cardinality: 114739 distinct values High cardinality
categories has a high cardinality: 83873 distinct values High cardinality
categories_tags has a high cardinality: 59303 distinct values High cardinality
categories_en has a high cardinality: 59303 distinct values High cardinality
origins has a high cardinality: 11140 distinct values High cardinality
origins_tags has a high cardinality: 9179 distinct values High cardinality
origins_en has a high cardinality: 9174 distinct values High cardinality
manufacturing_places has a high cardinality: 23746 distinct values High cardinality
manufacturing_places_tags has a high cardinality: 21432 distinct values High cardinality
labels has a high cardinality: 67759 distinct values High cardinality
labels_tags has a high cardinality: 49252 distinct values High cardinality
labels_en has a high cardinality: 49195 distinct values High cardinality
first_packaging_code_geo has a high cardinality: 3490 distinct values High cardinality
cities_tags has a high cardinality: 6530 distinct values High cardinality
purchase_places has a high cardinality: 10335 distinct values High cardinality
stores has a high cardinality: 12920 distinct values High cardinality
countries has a high cardinality: 8682 distinct values High cardinality
countries_tags has a high cardinality: 3214 distinct values High cardinality
countries_en has a high cardinality: 3214 distinct values High cardinality
ingredients_text has a high cardinality: 548597 distinct values High cardinality
allergens has a high cardinality: 6381 distinct values High cardinality
traces has a high cardinality: 10115 distinct values High cardinality
traces_tags has a high cardinality: 10210 distinct values High cardinality
traces_en has a high cardinality: 10210 distinct values High cardinality
serving_size has a high cardinality: 45137 distinct values High cardinality
additives_tags has a high cardinality: 89363 distinct values High cardinality
additives_en has a high cardinality: 89363 distinct values High cardinality
ingredients_that_may_be_from_palm_oil_tags has a high cardinality: 328 distinct values High cardinality
states has a high cardinality: 2877 distinct values High cardinality
states_tags has a high cardinality: 2877 distinct values High cardinality
states_en has a high cardinality: 2877 distinct values High cardinality
brand_owner has a high cardinality: 25553 distinct values High cardinality
main_category has a high cardinality: 26724 distinct values High cardinality
main_category_en has a high cardinality: 26723 distinct values High cardinality
product_name has 74697 (4.9%) missing values Missing
generic_name has 1417589 (93.0%) missing values Missing
quantity has 1101858 (72.3%) missing values Missing
packaging has 1282365 (84.1%) missing values Missing
packaging_tags has 1282376 (84.1%) missing values Missing
packaging_text has 1523939 (> 99.9%) missing values Missing
brands has 677434 (44.4%) missing values Missing
brands_tags has 677489 (44.4%) missing values Missing
categories has 745084 (48.9%) missing values Missing
categories_tags has 745084 (48.9%) missing values Missing
categories_en has 745084 (48.9%) missing values Missing
origins has 1459393 (95.7%) missing values Missing
origins_tags has 1459501 (95.7%) missing values Missing
origins_en has 1459501 (95.7%) missing values Missing
manufacturing_places has 1421577 (93.2%) missing values Missing
manufacturing_places_tags has 1421620 (93.2%) missing values Missing
labels has 1178669 (77.3%) missing values Missing
labels_tags has 1178645 (77.3%) missing values Missing
labels_en has 1178645 (77.3%) missing values Missing
emb_codes has 1422456 (93.3%) missing values Missing
emb_codes_tags has 1422485 (93.3%) missing values Missing
first_packaging_code_geo has 1460467 (95.8%) missing values Missing
cities has 1524579 (100.0%) missing values Missing
cities_tags has 1455436 (95.5%) missing values Missing
purchase_places has 1382233 (90.7%) missing values Missing
stores has 1314317 (86.2%) missing values Missing
ingredients_text has 868795 (57.0%) missing values Missing
allergens has 1350981 (88.6%) missing values Missing
allergens_en has 1524579 (100.0%) missing values Missing
traces has 1439063 (94.4%) missing values Missing
traces_tags has 1417076 (92.9%) missing values Missing
traces_en has 1417076 (92.9%) missing values Missing
serving_size has 1078152 (70.7%) missing values Missing
serving_quantity has 1077360 (70.7%) missing values Missing
no_nutriments has 1524579 (100.0%) missing values Missing
additives_n has 868794 (57.0%) missing values Missing
additives has 1524579 (100.0%) missing values Missing
additives_tags has 1143493 (75.0%) missing values Missing
additives_en has 1143493 (75.0%) missing values Missing
ingredients_from_palm_oil_n has 868794 (57.0%) missing values Missing
ingredients_from_palm_oil has 1524579 (100.0%) missing values Missing
ingredients_from_palm_oil_tags has 1511126 (99.1%) missing values Missing
ingredients_that_may_be_from_palm_oil_n has 868794 (57.0%) missing values Missing
ingredients_that_may_be_from_palm_oil has 1524579 (100.0%) missing values Missing
ingredients_that_may_be_from_palm_oil_tags has 1485860 (97.5%) missing values Missing
nutriscore_score has 914694 (60.0%) missing values Missing
nutriscore_grade has 914694 (60.0%) missing values Missing
nova_group has 951023 (62.4%) missing values Missing
pnns_groups_1 has 15376 (1.0%) missing values Missing
brand_owner has 1235298 (81.0%) missing values Missing
main_category has 745084 (48.9%) missing values Missing
main_category_en has 745084 (48.9%) missing values Missing
image_url has 436306 (28.6%) missing values Missing
image_small_url has 436306 (28.6%) missing values Missing
image_ingredients_url has 884840 (58.0%) missing values Missing
image_ingredients_small_url has 884840 (58.0%) missing values Missing
image_nutrition_url has 867873 (56.9%) missing values Missing
image_nutrition_small_url has 867873 (56.9%) missing values Missing
energy-kj_100g has 1412889 (92.7%) missing values Missing
energy-kcal_100g has 372176 (24.4%) missing values Missing
energy_100g has 304182 (20.0%) missing values Missing
energy-from-fat_100g has 1523610 (99.9%) missing values Missing
fat_100g has 313681 (20.6%) missing values Missing
saturated-fat_100g has 359896 (23.6%) missing values Missing
-butyric-acid_100g has 1524574 (> 99.9%) missing values Missing
-caproic-acid_100g has 1524578 (> 99.9%) missing values Missing
-caprylic-acid_100g has 1524577 (> 99.9%) missing values Missing
-capric-acid_100g has 1524575 (> 99.9%) missing values Missing
-lauric-acid_100g has 1524570 (> 99.9%) missing values Missing
-myristic-acid_100g has 1524578 (> 99.9%) missing values Missing
-palmitic-acid_100g has 1524576 (> 99.9%) missing values Missing
-stearic-acid_100g has 1524578 (> 99.9%) missing values Missing
-arachidic-acid_100g has 1524532 (> 99.9%) missing values Missing
-behenic-acid_100g has 1524560 (> 99.9%) missing values Missing
-lignoceric-acid_100g has 1524579 (100.0%) missing values Missing
-cerotic-acid_100g has 1524575 (> 99.9%) missing values Missing
-montanic-acid_100g has 1524577 (> 99.9%) missing values Missing
-melissic-acid_100g has 1524579 (100.0%) missing values Missing
monounsaturated-fat_100g has 1477942 (96.9%) missing values Missing
polyunsaturated-fat_100g has 1477914 (96.9%) missing values Missing
omega-3-fat_100g has 1522719 (99.9%) missing values Missing
-alpha-linolenic-acid_100g has 1524177 (> 99.9%) missing values Missing
-eicosapentaenoic-acid_100g has 1524467 (> 99.9%) missing values Missing
-docosahexaenoic-acid_100g has 1524426 (> 99.9%) missing values Missing
omega-6-fat_100g has 1524134 (> 99.9%) missing values Missing
-linoleic-acid_100g has 1524365 (> 99.9%) missing values Missing
-arachidonic-acid_100g has 1524530 (> 99.9%) missing values Missing
-gamma-linolenic-acid_100g has 1524574 (> 99.9%) missing values Missing
-dihomo-gamma-linolenic-acid_100g has 1524578 (> 99.9%) missing values Missing
omega-9-fat_100g has 1524527 (> 99.9%) missing values Missing
-oleic-acid_100g has 1524556 (> 99.9%) missing values Missing
-elaidic-acid_100g has 1524579 (100.0%) missing values Missing
-gondoic-acid_100g has 1524579 (100.0%) missing values Missing
-mead-acid_100g has 1524579 (100.0%) missing values Missing
-erucic-acid_100g has 1524579 (100.0%) missing values Missing
-nervonic-acid_100g has 1524579 (100.0%) missing values Missing
trans-fat_100g has 1260475 (82.7%) missing values Missing
cholesterol_100g has 1256522 (82.4%) missing values Missing
carbohydrates_100g has 314259 (20.6%) missing values Missing
sugars_100g has 335417 (22.0%) missing values Missing
-sucrose_100g has 1524451 (> 99.9%) missing values Missing
-glucose_100g has 1524525 (> 99.9%) missing values Missing
-fructose_100g has 1524504 (> 99.9%) missing values Missing
-lactose_100g has 1523879 (> 99.9%) missing values Missing
-maltose_100g has 1524570 (> 99.9%) missing values Missing
-maltodextrins_100g has 1524562 (> 99.9%) missing values Missing
starch_100g has 1524128 (> 99.9%) missing values Missing
polyols_100g has 1521095 (99.8%) missing values Missing
fiber_100g has 1071773 (70.3%) missing values Missing
-soluble-fiber_100g has 1520979 (99.8%) missing values Missing
-insoluble-fiber_100g has 1521249 (99.8%) missing values Missing
proteins_100g has 312602 (20.5%) missing values Missing
casein_100g has 1524538 (> 99.9%) missing values Missing
serum-proteins_100g has 1524542 (> 99.9%) missing values Missing
nucleotides_100g has 1524565 (> 99.9%) missing values Missing
salt_100g has 338988 (22.2%) missing values Missing
sodium_100g has 338993 (22.2%) missing values Missing
alcohol_100g has 1507229 (98.9%) missing values Missing
vitamin-a_100g has 1312667 (86.1%) missing values Missing
beta-carotene_100g has 1524498 (> 99.9%) missing values Missing
vitamin-d_100g has 1515370 (99.4%) missing values Missing
vitamin-e_100g has 1521501 (99.8%) missing values Missing
vitamin-k_100g has 1523502 (99.9%) missing values Missing
vitamin-c_100g has 1305092 (85.6%) missing values Missing
vitamin-b1_100g has 1501394 (98.5%) missing values Missing
vitamin-b2_100g has 1502296 (98.5%) missing values Missing
vitamin-pp_100g has 1501184 (98.5%) missing values Missing
vitamin-b6_100g has 1508950 (99.0%) missing values Missing
vitamin-b9_100g has 1514685 (99.4%) missing values Missing
folates_100g has 1516152 (99.4%) missing values Missing
vitamin-b12_100g has 1512258 (99.2%) missing values Missing
biotin_100g has 1523610 (99.9%) missing values Missing
pantothenic-acid_100g has 1518705 (99.6%) missing values Missing
silica_100g has 1524468 (> 99.9%) missing values Missing
bicarbonate_100g has 1524218 (> 99.9%) missing values Missing
potassium_100g has 1433088 (94.0%) missing values Missing
chloride_100g has 1523932 (> 99.9%) missing values Missing
calcium_100g has 1255649 (82.4%) missing values Missing
phosphorus_100g has 1511077 (99.1%) missing values Missing
iron_100g has 1260498 (82.7%) missing values Missing
magnesium_100g has 1510148 (99.1%) missing values Missing
zinc_100g has 1514575 (99.3%) missing values Missing
copper_100g has 1520367 (99.7%) missing values Missing
manganese_100g has 1520609 (99.7%) missing values Missing
fluoride_100g has 1524274 (> 99.9%) missing values Missing
selenium_100g has 1522177 (99.8%) missing values Missing
chromium_100g has 1524408 (> 99.9%) missing values Missing
molybdenum_100g has 1524352 (> 99.9%) missing values Missing
iodine_100g has 1522568 (99.9%) missing values Missing
caffeine_100g has 1524190 (> 99.9%) missing values Missing
taurine_100g has 1524439 (> 99.9%) missing values Missing
ph_100g has 1524410 (> 99.9%) missing values Missing
fruits-vegetables-nuts_100g has 1516062 (99.4%) missing values Missing
fruits-vegetables-nuts-dried_100g has 1524287 (> 99.9%) missing values Missing
fruits-vegetables-nuts-estimate_100g has 1512985 (99.2%) missing values Missing
collagen-meat-protein-ratio_100g has 1524272 (> 99.9%) missing values Missing
cocoa_100g has 1518915 (99.6%) missing values Missing
chlorophyl_100g has 1524576 (> 99.9%) missing values Missing
carbon-footprint_100g has 1524145 (> 99.9%) missing values Missing
carbon-footprint-from-meat-or-fish_100g has 1513553 (99.3%) missing values Missing
nutrition-score-fr_100g has 914694 (60.0%) missing values Missing
nutrition-score-uk_100g has 1524554 (> 99.9%) missing values Missing
glycemic-index_100g has 1524576 (> 99.9%) missing values Missing
water-hardness_100g has 1524579 (100.0%) missing values Missing
choline_100g has 1524540 (> 99.9%) missing values Missing
phylloquinone_100g has 1522867 (99.9%) missing values Missing
beta-glucan_100g has 1524554 (> 99.9%) missing values Missing
inositol_100g has 1524535 (> 99.9%) missing values Missing
carnitine_100g has 1524559 (> 99.9%) missing values Missing
serving_quantity is highly skewed (γ1 = 668.7443458) Skewed
energy-kj_100g is highly skewed (γ1 = 334.2005386) Skewed
energy-kcal_100g is highly skewed (γ1 = 1073.498221) Skewed
energy_100g is highly skewed (γ1 = 1104.715801) Skewed
fat_100g is highly skewed (γ1 = 1034.197371) Skewed
saturated-fat_100g is highly skewed (γ1 = 1079.2048) Skewed
omega-3-fat_100g is highly skewed (γ1 = 31.09222314) Skewed
trans-fat_100g is highly skewed (γ1 = 186.8116338) Skewed
cholesterol_100g is highly skewed (γ1 = 58.30991032) Skewed
fiber_100g is highly skewed (γ1 = 26.53871442) Skewed
proteins_100g is highly skewed (γ1 = 35.42074198) Skewed
salt_100g is highly skewed (γ1 = 735.3130733) Skewed
sodium_100g is highly skewed (γ1 = 735.8927624) Skewed
alcohol_100g is highly skewed (γ1 = 131.7193987) Skewed
vitamin-a_100g is highly skewed (γ1 = 249.7897214) Skewed
vitamin-d_100g is highly skewed (γ1 = 63.13562479) Skewed
vitamin-e_100g is highly skewed (γ1 = 21.20208075) Skewed
vitamin-k_100g is highly skewed (γ1 = 32.15805483) Skewed
vitamin-c_100g is highly skewed (γ1 = 74.79587134) Skewed
vitamin-b1_100g is highly skewed (γ1 = 42.62376456) Skewed
vitamin-b2_100g is highly skewed (γ1 = 71.83045853) Skewed
vitamin-pp_100g is highly skewed (γ1 = 61.83353601) Skewed
vitamin-b6_100g is highly skewed (γ1 = 47.78936151) Skewed
vitamin-b9_100g is highly skewed (γ1 = 33.62196279) Skewed
folates_100g is highly skewed (γ1 = 85.72656433) Skewed
vitamin-b12_100g is highly skewed (γ1 = 75.70509683) Skewed
biotin_100g is highly skewed (γ1 = 22.1109395) Skewed
pantothenic-acid_100g is highly skewed (γ1 = 40.94662316) Skewed
potassium_100g is highly skewed (γ1 = 66.35740207) Skewed
calcium_100g is highly skewed (γ1 = 116.1701179) Skewed
phosphorus_100g is highly skewed (γ1 = 41.58629645) Skewed
iron_100g is highly skewed (γ1 = 167.5003907) Skewed
magnesium_100g is highly skewed (γ1 = 49.72523335) Skewed
zinc_100g is highly skewed (γ1 = 55.17629642) Skewed
copper_100g is highly skewed (γ1 = 59.12314678) Skewed
manganese_100g is highly skewed (γ1 = 37.61503426) Skewed
selenium_100g is highly skewed (γ1 = 47.83093667) Skewed
iodine_100g is highly skewed (γ1 = 23.5446205) Skewed
carbon-footprint-from-meat-or-fish_100g is highly skewed (γ1 = 101.9364821) Skewed
phylloquinone_100g is highly skewed (γ1 = 28.34559835) Skewed
code is an unsupported type, check if it needs cleaning or further analysis Unsupported
emb_codes is an unsupported type, check if it needs cleaning or further analysis Unsupported
emb_codes_tags is an unsupported type, check if it needs cleaning or further analysis Unsupported
cities is an unsupported type, check if it needs cleaning or further analysis Unsupported
allergens_en is an unsupported type, check if it needs cleaning or further analysis Unsupported
no_nutriments is an unsupported type, check if it needs cleaning or further analysis Unsupported
additives is an unsupported type, check if it needs cleaning or further analysis Unsupported
ingredients_from_palm_oil is an unsupported type, check if it needs cleaning or further analysis Unsupported
ingredients_that_may_be_from_palm_oil is an unsupported type, check if it needs cleaning or further analysis Unsupported
-lignoceric-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
-melissic-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
-elaidic-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
-gondoic-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
-mead-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
-erucic-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
-nervonic-acid_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
water-hardness_100g is an unsupported type, check if it needs cleaning or further analysis Unsupported
additives_n has 274699 (18.0%) zeros Zeros
ingredients_that_may_be_from_palm_oil_n has 617066 (40.5%) zeros Zeros
nutriscore_score has 30887 (2.0%) zeros Zeros
energy-kcal_100g has 35624 (2.3%) zeros Zeros
energy_100g has 36131 (2.4%) zeros Zeros
fat_100g has 195507 (12.8%) zeros Zeros
saturated-fat_100g has 248203 (16.3%) zeros Zeros
trans-fat_100g has 258345 (16.9%) zeros Zeros
cholesterol_100g has 161260 (10.6%) zeros Zeros
carbohydrates_100g has 96377 (6.3%) zeros Zeros
sugars_100g has 169835 (11.1%) zeros Zeros
fiber_100g has 141660 (9.3%) zeros Zeros
proteins_100g has 161390 (10.6%) zeros Zeros
salt_100g has 169618 (11.1%) zeros Zeros
sodium_100g has 169613 (11.1%) zeros Zeros
vitamin-a_100g has 118140 (7.7%) zeros Zeros
vitamin-c_100g has 136210 (8.9%) zeros Zeros
calcium_100g has 84863 (5.6%) zeros Zeros
iron_100g has 79661 (5.2%) zeros Zeros
nutrition-score-fr_100g has 30887 (2.0%) zeros Zeros

Reproduction

Analysis started2020-12-04 08:35:26.548639
Analysis finished2020-12-04 08:38:31.479685
Duration3 minutes and 4.93 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

code
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size11.6 MiB

url
URL

Distinct1524570
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size11.6 MiB
http://world-en.openfoodfacts.org/product/4770175482692/the-queen-s
 
2
http://world-en.openfoodfacts.org/product/6191531900922/flocons-d-avoine-vita-fibres
 
2
http://world-en.openfoodfacts.org/product/3220440176203/la-laitiere-lait-d-amande-pepites-facon-calisson-nestle
 
2
http://world-en.openfoodfacts.org/product/3261830123377/lot-de-3-pate-de-foie-stephan
 
2
http://world-en.openfoodfacts.org/product/2210248030310/jambon-cuit-superieur-3-noix
 
2
Other values (1524565)
1524569 
ValueCountFrequency (%) 
http://world-en.openfoodfacts.org/product/4770175482692/the-queen-s2< 0.1%
 
http://world-en.openfoodfacts.org/product/6191531900922/flocons-d-avoine-vita-fibres2< 0.1%
 
http://world-en.openfoodfacts.org/product/3220440176203/la-laitiere-lait-d-amande-pepites-facon-calisson-nestle2< 0.1%
 
http://world-en.openfoodfacts.org/product/3261830123377/lot-de-3-pate-de-foie-stephan2< 0.1%
 
http://world-en.openfoodfacts.org/product/2210248030310/jambon-cuit-superieur-3-noix2< 0.1%
 
http://world-en.openfoodfacts.org/product/3760275520791/cafe-moulu2< 0.1%
 
http://world-en.openfoodfacts.org/product/3760228431501/creme-glacee-au-lait-frais2< 0.1%
 
http://world-en.openfoodfacts.org/product/56905220075162< 0.1%
 
http://world-en.openfoodfacts.org/product/5410827031715/saucisson-de-cheval-rouge-fume-fecule-sans-marque2< 0.1%
 
http://world-en.openfoodfacts.org/product/3283040010742/jambon-cheddar-roquette-entracte1< 0.1%
 
Other values (1524560)1524560> 99.9%
 
ValueCountFrequency (%) 
http1524579100.0%
 
ValueCountFrequency (%) 
world-en.openfoodfacts.org1524579100.0%
 
ValueCountFrequency (%) 
/product/2210248030310/jambon-cuit-superieur-3-noix2< 0.1%
 
/product/6191531900922/flocons-d-avoine-vita-fibres2< 0.1%
 
/product/3220440176203/la-laitiere-lait-d-amande-pepites-facon-calisson-nestle2< 0.1%
 
/product/3760275520791/cafe-moulu2< 0.1%
 
/product/4770175482692/the-queen-s2< 0.1%
 
/product/5410827031715/saucisson-de-cheval-rouge-fume-fecule-sans-marque2< 0.1%
 
/product/3760228431501/creme-glacee-au-lait-frais2< 0.1%
 
/product/56905220075162< 0.1%
 
/product/3261830123377/lot-de-3-pate-de-foie-stephan2< 0.1%
 
/product/0856676006040/organic-mixed-vegetables1< 0.1%
 
Other values (1524560)1524560> 99.9%
 
ValueCountFrequency (%) 
1524579100.0%
 
ValueCountFrequency (%) 
1524579100.0%
 

creator
Categorical

HIGH CARDINALITY

Distinct12355
Distinct (%)0.8%
Missing4
Missing (%)< 0.1%
Memory size11.6 MiB
kiliweb
805454 
usda-ndb-import
169834 
openfoodfacts-contributors
153294 
org-database-usda
134540 
date-limite-app
 
31170
Other values (12350)
230283 
ValueCountFrequency (%) 
kiliweb80545452.8%
 
usda-ndb-import16983411.1%
 
openfoodfacts-contributors15329410.1%
 
org-database-usda1345408.8%
 
date-limite-app311702.0%
 
elcoco295941.9%
 
openfood-ch-import114560.8%
 
sebleouf102690.7%
 
tacite86180.6%
 
prepperapp82590.5%
 
Other values (12345)16208710.6%
 
2020-12-04T09:38:39.254953image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6499 ?
Unique (%)0.4%

created_t
Real number (ℝ≥0)

Distinct1276844
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1541741676
Minimum1328021038
Maximum1605696095
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:38:40.018391image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1328021038
5-th percentile1461174869
Q11512327644
median1551207563
Q31581549964
95-th percentile1598649444
Maximum1605696095
Range277675057
Interquartile range (IQR)69222320

Descriptive statistics

Standard deviation46947527.2
Coefficient of variation (CV)0.03045096849
Kurtosis1.123384685
Mean1541741676
Median Absolute Deviation (MAD)33351457
Skewness-0.9993119885
Sum2.350506982e+15
Variance2.20407031e+15
MonotocityNot monotonic
2020-12-04T09:38:40.200421image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
158766252728< 0.1%
 
158766620127< 0.1%
 
158765643223< 0.1%
 
158766285223< 0.1%
 
158766982322< 0.1%
 
158765643321< 0.1%
 
158766252121< 0.1%
 
158765985221< 0.1%
 
148905582920< 0.1%
 
148907712020< 0.1%
 
Other values (1276834)1524353> 99.9%
 
ValueCountFrequency (%) 
13280210381< 0.1%
 
13287836961< 0.1%
 
13289718671< 0.1%
 
13289728431< 0.1%
 
13289863181< 0.1%
 
ValueCountFrequency (%) 
16056960951< 0.1%
 
16056957501< 0.1%
 
16056955681< 0.1%
 
16056955071< 0.1%
 
16056954341< 0.1%
 

created_datetime
Categorical

HIGH CARDINALITY

Distinct1276844
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size11.6 MiB
2020-04-23T17:22:07Z
 
28
2020-04-23T18:23:21Z
 
27
2020-04-23T15:40:32Z
 
23
2020-04-23T17:27:32Z
 
23
2020-04-23T19:23:43Z
 
22
Other values (1276839)
1524456 
ValueCountFrequency (%) 
2020-04-23T17:22:07Z28< 0.1%
 
2020-04-23T18:23:21Z27< 0.1%
 
2020-04-23T15:40:32Z23< 0.1%
 
2020-04-23T17:27:32Z23< 0.1%
 
2020-04-23T19:23:43Z22< 0.1%
 
2020-04-23T15:40:33Z21< 0.1%
 
2020-04-23T17:22:01Z21< 0.1%
 
2020-04-23T16:37:32Z21< 0.1%
 
2017-03-09T16:32:00Z20< 0.1%
 
2017-03-09T10:37:09Z20< 0.1%
 
Other values (1276834)1524353> 99.9%
 
2020-12-04T09:38:47.965282image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1195068 ?
Unique (%)78.4%

last_modified_t
Real number (ℝ≥0)

Distinct1164947
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1576448094
Minimum1333872755
Maximum1605696098
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:38:48.690964image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1333872755
5-th percentile1523295414
Q11566591940
median1586692989
Q31591159886
95-th percentile1603793356
Maximum1605696098
Range271823343
Interquartile range (IQR)24567946.5

Descriptive statistics

Standard deviation26750486.14
Coefficient of variation (CV)0.01696883407
Kurtosis6.464984657
Mean1576448094
Median Absolute Deviation (MAD)10641234
Skewness-2.153403302
Sum2.403419659e+15
Variance7.155885085e+14
MonotocityNot monotonic
2020-12-04T09:38:48.858635image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
155277088778< 0.1%
 
160320822867< 0.1%
 
160545668460< 0.1%
 
154999669360< 0.1%
 
155277088560< 0.1%
 
160485465056< 0.1%
 
160536693455< 0.1%
 
156995517554< 0.1%
 
154999669154< 0.1%
 
155277088652< 0.1%
 
Other values (1164937)1523983> 99.9%
 
ValueCountFrequency (%) 
13338727551< 0.1%
 
13346960081< 0.1%
 
13365201751< 0.1%
 
13386501351< 0.1%
 
13387289531< 0.1%
 
ValueCountFrequency (%) 
16056960981< 0.1%
 
16056960851< 0.1%
 
16056957521< 0.1%
 
16056957451< 0.1%
 
16056957031< 0.1%
 

last_modified_datetime
Categorical

HIGH CARDINALITY

Distinct1164947
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size11.6 MiB
2019-03-16T21:14:47Z
 
78
2020-10-20T15:37:08Z
 
67
2019-03-16T21:14:45Z
 
60
2019-02-12T18:38:13Z
 
60
2020-11-15T16:11:24Z
 
60
Other values (1164942)
1524254 
ValueCountFrequency (%) 
2019-03-16T21:14:47Z78< 0.1%
 
2020-10-20T15:37:08Z67< 0.1%
 
2019-03-16T21:14:45Z60< 0.1%
 
2019-02-12T18:38:13Z60< 0.1%
 
2020-11-15T16:11:24Z60< 0.1%
 
2020-11-08T16:57:30Z56< 0.1%
 
2020-11-14T15:15:34Z55< 0.1%
 
2019-02-12T18:38:11Z54< 0.1%
 
2019-10-01T18:39:35Z54< 0.1%
 
2019-03-16T21:14:46Z52< 0.1%
 
Other values (1164937)1523983> 99.9%
 
2020-12-04T09:38:54.187145image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1024106 ?
Unique (%)67.2%

product_name
Categorical

HIGH CARDINALITY
MISSING

Distinct967856
Distinct (%)66.8%
Missing74697
Missing (%)4.9%
Memory size11.6 MiB
Aceite de oliva virgen extra
 
1039
Miel
 
1035
Filet de poulet
 
880
Comté
 
837
Ice cream
 
737
Other values (967851)
1445354 
ValueCountFrequency (%) 
Aceite de oliva virgen extra10390.1%
 
Miel10350.1%
 
Filet de poulet8800.1%
 
Comté8370.1%
 
Ice cream737< 0.1%
 
Emmental604< 0.1%
 
Huile d'olive585< 0.1%
 
Mayonnaise561< 0.1%
 
Chocolat557< 0.1%
 
Jus de pomme541< 0.1%
 
Other values (967846)144250694.6%
 
(Missing)746974.9%
 
2020-12-04T09:38:59.072253image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique851835 ?
Unique (%)58.8%

generic_name
Categorical

HIGH CARDINALITY
MISSING

Distinct78579
Distinct (%)73.4%
Missing1417589
Missing (%)93.0%
Memory size11.6 MiB
Ice cream
 
180
Pâtes alimentaires au blé dur de qualité supérieure
 
168
Pâtes alimentaires de qualité supérieure
 
143
Beignets fourrés à la purée de framboise
 
122
Bière
 
116
Other values (78574)
106261 
ValueCountFrequency (%) 
Ice cream180< 0.1%
 
Pâtes alimentaires au blé dur de qualité supérieure168< 0.1%
 
Pâtes alimentaires de qualité supérieure143< 0.1%
 
Beignets fourrés à la purée de framboise122< 0.1%
 
Bière116< 0.1%
 
Beignets fourrés à la purée de pomme113< 0.1%
 
Jambon cuit supérieur104< 0.1%
 
Aliment pour bébés93< 0.1%
 
Chocolat noir90< 0.1%
 
Jus d'orange88< 0.1%
 
Other values (78569)1057736.9%
 
(Missing)141758993.0%
 
2020-12-04T09:38:59.460093image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique69133 ?
Unique (%)64.6%

quantity
Categorical

HIGH CARDINALITY
MISSING

Distinct33349
Distinct (%)7.9%
Missing1101858
Missing (%)72.3%
Memory size11.6 MiB
500 g
 
18575
200 g
 
16422
250 g
 
16311
100 g
 
12477
400 g
 
10819
Other values (33344)
348117 
ValueCountFrequency (%) 
500 g185751.2%
 
200 g164221.1%
 
250 g163111.1%
 
100 g124770.8%
 
400 g108190.7%
 
300 g99200.7%
 
150 g97500.6%
 
1 kg76050.5%
 
125 g57070.4%
 
500g54320.4%
 
Other values (33339)30970320.3%
 
(Missing)110185872.3%
 
2020-12-04T09:38:59.708590image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique23814 ?
Unique (%)5.6%

packaging
Categorical

HIGH CARDINALITY
MISSING

Distinct42038
Distinct (%)17.4%
Missing1282365
Missing (%)84.1%
Memory size11.6 MiB
Kunststoff
 
5040
sachet,plastique
 
4508
plastique
 
4100
Sachet,Plastique
 
3581
Glas
 
3515
Other values (42033)
221470 
ValueCountFrequency (%) 
Kunststoff50400.3%
 
sachet,plastique45080.3%
 
plastique41000.3%
 
Sachet,Plastique35810.2%
 
Glas35150.2%
 
sachet35080.2%
 
Plastique35030.2%
 
Bouteille,Verre30500.2%
 
Frais27620.2%
 
Carton27290.2%
 
Other values (42028)20591813.5%
 
(Missing)128236584.1%
 
2020-12-04T09:38:59.979406image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique32079 ?
Unique (%)13.2%

packaging_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct33985
Distinct (%)14.0%
Missing1282376
Missing (%)84.1%
Memory size11.6 MiB
sachet,plastique
 
9196
plastique
 
7626
kunststoff
 
5310
carton
 
5150
plastic
 
4730
Other values (33980)
210191 
ValueCountFrequency (%) 
sachet,plastique91960.6%
 
plastique76260.5%
 
kunststoff53100.3%
 
carton51500.3%
 
plastic47300.3%
 
sachet45740.3%
 
bouteille,verre40630.3%
 
glas40530.3%
 
conserve36100.2%
 
frais31760.2%
 
Other values (33975)19071512.5%
 
(Missing)128237684.1%
 
2020-12-04T09:39:00.223472image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique25465 ?
Unique (%)10.5%

packaging_text
Categorical

HIGH CARDINALITY
MISSING

Distinct471
Distinct (%)73.6%
Missing1523939
Missing (%)> 99.9%
Memory size11.6 MiB
Colored plastic package
 
13
Einweg
 
12
Grüner Punkt
 
9
Colored Plastic
 
8
Not Yet Recycled
 
8
Other values (466)
590 
ValueCountFrequency (%) 
Colored plastic package13< 0.1%
 
Einweg12< 0.1%
 
Grüner Punkt9< 0.1%
 
Colored Plastic8< 0.1%
 
Not Yet Recycled8< 0.1%
 
1 pot en verre à recycler8< 0.1%
 
41 ALU7< 0.1%
 
Pot verre à recyclé, couvercle métal à recyclé7< 0.1%
 
Sorteras som plastförpackning.7< 0.1%
 
Not Yet Recycled.7< 0.1%
 
Other values (461)554< 0.1%
 
(Missing)1523939> 99.9%
 
2020-12-04T09:39:00.392078image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique400 ?
Unique (%)62.5%

brands
Categorical

HIGH CARDINALITY
MISSING

Distinct146872
Distinct (%)17.3%
Missing677434
Missing (%)44.4%
Memory size11.6 MiB
Carrefour
 
13226
Auchan
 
10952
U
 
6029
Bonarea
 
5537
Delhaize
 
4866
Other values (146867)
806535 
ValueCountFrequency (%) 
Carrefour132260.9%
 
Auchan109520.7%
 
U60290.4%
 
Bonarea55370.4%
 
Delhaize48660.3%
 
Hacendado46730.3%
 
Casino44260.3%
 
Nestlé43450.3%
 
Leader Price41240.3%
 
Cora33790.2%
 
Other values (146862)78558851.5%
 
(Missing)67743444.4%
 
2020-12-04T09:39:00.968746image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique94000 ?
Unique (%)11.1%

brands_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct114739
Distinct (%)13.5%
Missing677489
Missing (%)44.4%
Memory size11.6 MiB
carrefour
 
13876
auchan
 
11406
bonarea
 
6168
u
 
6084
nestle
 
5313
Other values (114734)
804243 
ValueCountFrequency (%) 
carrefour138760.9%
 
auchan114060.7%
 
bonarea61680.4%
 
u60840.4%
 
nestle53130.3%
 
hacendado50100.3%
 
delhaize49490.3%
 
casino45140.3%
 
leader-price45000.3%
 
coop36590.2%
 
Other values (114729)78161151.3%
 
(Missing)67748944.4%
 
2020-12-04T09:39:01.463259image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique68248 ?
Unique (%)8.1%

categories
Categorical

HIGH CARDINALITY
MISSING

Distinct83873
Distinct (%)10.8%
Missing745084
Missing (%)48.9%
Memory size11.6 MiB
Snacks
 
32709
Snacks, Sweet snacks, Confectioneries
 
14353
Groceries, Sauces
 
13921
Dairies, Fermented foods, Fermented milk products, Cheeses
 
11394
Snacks, Sweet snacks, Biscuits and cakes, Biscuits
 
10100
Other values (83868)
697018 
ValueCountFrequency (%) 
Snacks327092.1%
 
Snacks, Sweet snacks, Confectioneries143530.9%
 
Groceries, Sauces139210.9%
 
Dairies, Fermented foods, Fermented milk products, Cheeses113940.7%
 
Snacks, Sweet snacks, Biscuits and cakes, Biscuits101000.7%
 
Desserts, Frozen foods, Frozen desserts91210.6%
 
Plant-based foods and beverages, Plant-based foods, Cereals and potatoes, Breads70860.5%
 
Frozen foods69200.5%
 
Plant-based foods and beverages, Plant-based foods, Cereals and potatoes, Cereals and their products68220.4%
 
Salted snacks67740.4%
 
Other values (83863)66029543.3%
 
(Missing)74508448.9%
 
2020-12-04T09:39:01.922588image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique56185 ?
Unique (%)7.2%

categories_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct59303
Distinct (%)7.6%
Missing745084
Missing (%)48.9%
Memory size11.6 MiB
en:snacks
 
32858
en:groceries,en:sauces
 
15636
en:snacks,en:sweet-snacks,en:confectioneries
 
15046
en:dairies,en:fermented-foods,en:fermented-milk-products,en:cheeses
 
14019
en:snacks,en:sweet-snacks,en:biscuits-and-cakes,en:biscuits
 
13908
Other values (59298)
688028 
ValueCountFrequency (%) 
en:snacks328582.2%
 
en:groceries,en:sauces156361.0%
 
en:snacks,en:sweet-snacks,en:confectioneries150461.0%
 
en:dairies,en:fermented-foods,en:fermented-milk-products,en:cheeses140190.9%
 
en:snacks,en:sweet-snacks,en:biscuits-and-cakes,en:biscuits139080.9%
 
en:beverages92220.6%
 
en:desserts,en:frozen-foods,en:frozen-desserts92100.6%
 
en:plant-based-foods-and-beverages,en:plant-based-foods,en:cereals-and-potatoes,en:breads86890.6%
 
en:plant-based-foods-and-beverages,en:plant-based-foods,en:cereals-and-potatoes,en:cereals-and-their-products73070.5%
 
en:frozen-foods71590.5%
 
Other values (59293)64644142.4%
 
(Missing)74508448.9%
 
2020-12-04T09:39:02.307454image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique40635 ?
Unique (%)5.2%

categories_en
Categorical

HIGH CARDINALITY
MISSING

Distinct59303
Distinct (%)7.6%
Missing745084
Missing (%)48.9%
Memory size11.6 MiB
Snacks
 
32858
Groceries,Sauces
 
15636
Snacks,Sweet snacks,Confectioneries
 
15046
Dairies,Fermented foods,Fermented milk products,Cheeses
 
14019
Snacks,Sweet snacks,Biscuits and cakes,Biscuits
 
13908
Other values (59298)
688028 
ValueCountFrequency (%) 
Snacks328582.2%
 
Groceries,Sauces156361.0%
 
Snacks,Sweet snacks,Confectioneries150461.0%
 
Dairies,Fermented foods,Fermented milk products,Cheeses140190.9%
 
Snacks,Sweet snacks,Biscuits and cakes,Biscuits139080.9%
 
Beverages92220.6%
 
Desserts,Frozen foods,Frozen desserts92100.6%
 
Plant-based foods and beverages,Plant-based foods,Cereals and potatoes,Breads86890.6%
 
Plant-based foods and beverages,Plant-based foods,Cereals and potatoes,Cereals and their products73070.5%
 
Frozen foods71590.5%
 
Other values (59293)64644142.4%
 
(Missing)74508448.9%
 
2020-12-04T09:39:02.727595image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique40635 ?
Unique (%)5.2%

origins
Categorical

HIGH CARDINALITY
MISSING

Distinct11140
Distinct (%)17.1%
Missing1459393
Missing (%)95.7%
Memory size11.6 MiB
France
15262 
México
 
1859
Union Européenne
 
1657
España
 
1309
Italie
 
1280
Other values (11135)
43819 
ValueCountFrequency (%) 
France152621.0%
 
México18590.1%
 
Union Européenne16570.1%
 
España13090.1%
 
Italie12800.1%
 
Espagne12460.1%
 
Union européenne8390.1%
 
Deutschland8340.1%
 
Polska7670.1%
 
Suisse622< 0.1%
 
Other values (11130)395112.6%
 
(Missing)145939395.7%
 
2020-12-04T09:39:02.936380image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique8743 ?
Unique (%)13.4%

origins_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct9179
Distinct (%)14.1%
Missing1459501
Missing (%)95.7%
Memory size11.6 MiB
en:france
15791 
en:european-union
 
3220
en:spain
 
2979
en:mexico
 
2706
en:italy
 
2482
Other values (9174)
37900 
ValueCountFrequency (%) 
en:france157911.0%
 
en:european-union32200.2%
 
en:spain29790.2%
 
en:mexico27060.2%
 
en:italy24820.2%
 
en:germany12690.1%
 
en:poland9350.1%
 
en:switzerland8900.1%
 
en:united-states693< 0.1%
 
en:china621< 0.1%
 
Other values (9169)334922.2%
 
(Missing)145950195.7%
 
2020-12-04T09:39:03.137758image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7130 ?
Unique (%)11.0%

origins_en
Categorical

HIGH CARDINALITY
MISSING

Distinct9174
Distinct (%)14.1%
Missing1459501
Missing (%)95.7%
Memory size11.6 MiB
France
15798 
European Union
 
3220
Spain
 
2980
Mexico
 
2706
Italy
 
2482
Other values (9169)
37892 
ValueCountFrequency (%) 
France157981.0%
 
European Union32200.2%
 
Spain29800.2%
 
Mexico27060.2%
 
Italy24820.2%
 
Germany12690.1%
 
Poland9350.1%
 
Switzerland8900.1%
 
United States694< 0.1%
 
China621< 0.1%
 
Other values (9164)334832.2%
 
(Missing)145950195.7%
 
2020-12-04T09:39:03.331693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7125 ?
Unique (%)10.9%

manufacturing_places
Categorical

HIGH CARDINALITY
MISSING

Distinct23746
Distinct (%)23.1%
Missing1421577
Missing (%)93.2%
Memory size11.6 MiB
France
22069 
Italie
 
2878
Deutschland
 
2155
Belgique
 
1706
Suisse
 
1602
Other values (23741)
72592 
ValueCountFrequency (%) 
France220691.4%
 
Italie28780.2%
 
Deutschland21550.1%
 
Belgique17060.1%
 
Suisse16020.1%
 
Allemagne15830.1%
 
Espagne12860.1%
 
España12650.1%
 
México10390.1%
 
United Kingdom9600.1%
 
Other values (23736)664594.4%
 
(Missing)142157793.2%
 
2020-12-04T09:39:03.546991image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique18660 ?
Unique (%)18.1%

manufacturing_places_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct21432
Distinct (%)20.8%
Missing1421620
Missing (%)93.2%
Memory size11.6 MiB
france
23019 
italie
 
3060
deutschland
 
2172
belgique
 
1773
suisse
 
1714
Other values (21427)
71221 
ValueCountFrequency (%) 
france230191.5%
 
italie30600.2%
 
deutschland21720.1%
 
belgique17730.1%
 
suisse17140.1%
 
allemagne16390.1%
 
mexico16070.1%
 
espagne13550.1%
 
espana13550.1%
 
united-kingdom10040.1%
 
Other values (21422)642614.2%
 
(Missing)142162093.2%
 
2020-12-04T09:39:03.747343image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique16304 ?
Unique (%)15.8%

labels
Categorical

HIGH CARDINALITY
MISSING

Distinct67759
Distinct (%)19.6%
Missing1178669
Missing (%)77.3%
Memory size11.6 MiB
en:gluten-free
 
18857
Organic
 
16023
en:organic
 
11038
en:made-in-france
 
8435
en:no-preservatives
 
6598
Other values (67754)
284959 
ValueCountFrequency (%) 
en:gluten-free188571.2%
 
Organic160231.1%
 
en:organic110380.7%
 
en:made-in-france84350.6%
 
en:no-preservatives65980.4%
 
Bio 54130.4%
 
Point Vert52900.3%
 
en:vegan52690.3%
 
en:no-colorings45630.3%
 
Sin gluten34750.2%
 
Other values (67749)26094917.1%
 
(Missing)117866977.3%
 
2020-12-04T09:39:04.105455image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique53882 ?
Unique (%)15.6%

labels_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct49252
Distinct (%)14.2%
Missing1178645
Missing (%)77.3%
Memory size11.6 MiB
en:organic
34673 
en:gluten-free
 
25332
en:made-in-france
 
10496
en:green-dot
 
9251
en:vegetarian,en:vegan
 
8581
Other values (49247)
257601 
ValueCountFrequency (%) 
en:organic346732.3%
 
en:gluten-free253321.7%
 
en:made-in-france104960.7%
 
en:green-dot92510.6%
 
en:vegetarian,en:vegan85810.6%
 
en:no-preservatives84210.6%
 
en:no-colorings54550.4%
 
en:no-colorings,en:no-preservatives48960.3%
 
en:organic,en:eu-organic,fr:ab-agriculture-biologique45790.3%
 
en:no-added-sugar40960.3%
 
Other values (49242)23015415.1%
 
(Missing)117864577.3%
 
2020-12-04T09:39:04.411519image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique38335 ?
Unique (%)11.1%

labels_en
Categorical

HIGH CARDINALITY
MISSING

Distinct49195
Distinct (%)14.2%
Missing1178645
Missing (%)77.3%
Memory size11.6 MiB
Organic
34673 
Gluten-free
 
25332
Made in France
 
10496
Green Dot
 
9251
Vegetarian,Vegan
 
8581
Other values (49190)
257601 
ValueCountFrequency (%) 
Organic346732.3%
 
Gluten-free253321.7%
 
Made in France104960.7%
 
Green Dot92510.6%
 
Vegetarian,Vegan85810.6%
 
No preservatives84210.6%
 
Organic,EU Organic,AB Agriculture Biologique81170.5%
 
No colorings54550.4%
 
No colorings,No preservatives48960.3%
 
No added sugar40960.3%
 
Other values (49185)22661614.9%
 
(Missing)117864577.3%
 
2020-12-04T09:39:04.717054image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique38295 ?
Unique (%)11.1%

emb_codes
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1422456
Missing (%)93.3%
Memory size11.6 MiB

emb_codes_tags
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1422485
Missing (%)93.3%
Memory size11.6 MiB

first_packaging_code_geo
Categorical

HIGH CARDINALITY
MISSING

Distinct3490
Distinct (%)5.4%
Missing1460467
Missing (%)95.8%
Memory size11.6 MiB
47.833333,-0.333333
 
1103
49.083333,-0.65
 
567
47.633333,-2.666667
 
509
47.933333,-4.016667
 
455
48.116667,-1.4
 
420
Other values (3485)
61058 
ValueCountFrequency (%) 
47.833333,-0.33333311030.1%
 
49.083333,-0.65567< 0.1%
 
47.633333,-2.666667509< 0.1%
 
47.933333,-4.016667455< 0.1%
 
48.116667,-1.4420< 0.1%
 
47.766667,-3.233333400< 0.1%
 
45.666667,4.9395< 0.1%
 
48.1,-4.333333391< 0.1%
 
47.933333,-3.7382< 0.1%
 
49.266667,-0.666667378< 0.1%
 
Other values (3480)591123.9%
 
(Missing)146046795.8%
 
2020-12-04T09:39:04.889630image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1207 ?
Unique (%)1.9%

cities
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

cities_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct6530
Distinct (%)9.4%
Missing1455436
Missing (%)95.5%
Memory size11.6 MiB
sable-sur-sarthe-sarthe-france
 
861
theix-morbihan-france
 
487
saint-evarzec-finistere-france
 
389
chateaubourg-ille-et-vilaine-france
 
378
corbas-rhone-france
 
376
Other values (6525)
66652 
ValueCountFrequency (%) 
sable-sur-sarthe-sarthe-france8610.1%
 
theix-morbihan-france487< 0.1%
 
saint-evarzec-finistere-france389< 0.1%
 
chateaubourg-ille-et-vilaine-france378< 0.1%
 
corbas-rhone-france376< 0.1%
 
nueil-les-aubiers-deux-sevres-france369< 0.1%
 
douarnenez-finistere-france345< 0.1%
 
kervignac-morbihan-france345< 0.1%
 
villers-bocage-calvados-france343< 0.1%
 
boulogne-sur-mer-pas-de-calais-france315< 0.1%
 
Other values (6520)649354.3%
 
(Missing)145543695.5%
 
2020-12-04T09:39:05.057312image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3170 ?
Unique (%)4.6%

purchase_places
Categorical

HIGH CARDINALITY
MISSING

Distinct10335
Distinct (%)7.3%
Missing1382233
Missing (%)90.7%
Memory size11.6 MiB
France
40072 
Deutschland
 
6158
España
 
3843
Lyon,France
 
3389
Courrières,France
 
2451
Other values (10330)
86433 
ValueCountFrequency (%) 
France400722.6%
 
Deutschland61580.4%
 
España38430.3%
 
Lyon,France33890.2%
 
Courrières,France24510.2%
 
France,Nantes23910.2%
 
Paris,France21320.1%
 
Madrid,España21040.1%
 
Polska16560.1%
 
Belgique16540.1%
 
Other values (10325)764965.0%
 
(Missing)138223390.7%
 
2020-12-04T09:39:05.237854image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7123 ?
Unique (%)5.0%

stores
Categorical

HIGH CARDINALITY
MISSING

Distinct12920
Distinct (%)6.1%
Missing1314317
Missing (%)86.2%
Memory size11.6 MiB
Carrefour
15879 
Auchan
 
13078
Magasins U
 
13009
Leclerc
 
9045
Delhaize
 
8112
Other values (12915)
151139 
ValueCountFrequency (%) 
Carrefour158791.0%
 
Auchan130780.9%
 
Magasins U130090.9%
 
Leclerc90450.6%
 
Delhaize81120.5%
 
Lidl79190.5%
 
Intermarché57460.4%
 
Migros53820.4%
 
Casino51500.3%
 
Cora42890.3%
 
Other values (12910)1226538.0%
 
(Missing)131431786.2%
 
2020-12-04T09:39:05.443166image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9276 ?
Unique (%)4.4%

countries
Categorical

HIGH CARDINALITY

Distinct8682
Distinct (%)0.6%
Missing5117
Missing (%)0.3%
Memory size11.6 MiB
France
423606 
United States
309392 
en:fr
134148 
en:es
85008 
en:france
60682 
Other values (8677)
506626 
ValueCountFrequency (%) 
France42360627.8%
 
United States30939220.3%
 
en:fr1341488.8%
 
en:es850085.6%
 
en:france606824.0%
 
España580053.8%
 
en:FR270731.8%
 
en:be231891.5%
 
Deutschland164581.1%
 
en:Germany157091.0%
 
Other values (8672)36619224.0%
 
2020-12-04T09:39:05.631183image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique5056 ?
Unique (%)0.3%

countries_tags
Categorical

HIGH CARDINALITY

Distinct3214
Distinct (%)0.2%
Missing5121
Missing (%)0.3%
Memory size11.6 MiB
en:france
666307 
en:united-states
331950 
en:spain
172959 
en:belgium
 
41863
en:germany
 
39991
Other values (3209)
266388 
ValueCountFrequency (%) 
en:france66630743.7%
 
en:united-states33195021.8%
 
en:spain17295911.3%
 
en:belgium418632.7%
 
en:germany399912.6%
 
en:switzerland385082.5%
 
en:united-kingdom270511.8%
 
en:canada189831.2%
 
en:italy119740.8%
 
en:france,en:germany109870.7%
 
Other values (3204)15888510.4%
 
2020-12-04T09:39:05.796350image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1949 ?
Unique (%)0.1%

countries_en
Categorical

HIGH CARDINALITY

Distinct3214
Distinct (%)0.2%
Missing5121
Missing (%)0.3%
Memory size11.6 MiB
France
666307 
United States
331950 
Spain
172959 
Belgium
 
41863
Germany
 
39991
Other values (3209)
266388 
ValueCountFrequency (%) 
France66630743.7%
 
United States33195021.8%
 
Spain17295911.3%
 
Belgium418632.7%
 
Germany399912.6%
 
Switzerland385082.5%
 
United Kingdom270511.8%
 
Canada189831.2%
 
Italy119740.8%
 
France,Germany109870.7%
 
Other values (3204)15888510.4%
 
2020-12-04T09:39:05.969423image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1949 ?
Unique (%)0.1%

ingredients_text
Categorical

HIGH CARDINALITY
MISSING

Distinct548597
Distinct (%)83.7%
Missing868795
Missing (%)57.0%
Memory size11.6 MiB
Carbonated water, natural flavor.
 
475
Almonds.
 
392
Spring water, co2, natural flavors.
 
335
Extra virgin olive oil.
 
319
Semolina (wheat), durum flour (wheat), niacin, ferrous sulfate (iron), thiamin mononitrate, riboflavin, folic acid.
 
297
Other values (548592)
653966 
ValueCountFrequency (%) 
Carbonated water, natural flavor.475< 0.1%
 
Almonds.392< 0.1%
 
Spring water, co2, natural flavors.335< 0.1%
 
Extra virgin olive oil.319< 0.1%
 
Semolina (wheat), durum flour (wheat), niacin, ferrous sulfate (iron), thiamin mononitrate, riboflavin, folic acid.297< 0.1%
 
Miel270< 0.1%
 
Green beans, water, salt.266< 0.1%
 
Pasteurized milk, cheese culture, salt, enzymes, annatto (vegetable color).259< 0.1%
 
Pasteurized milk, cheese culture, salt, enzymes.251< 0.1%
 
Carbonated water, natural flavors.250< 0.1%
 
Other values (548587)65267042.8%
 
(Missing)86879557.0%
 
2020-12-04T09:39:08.559575image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique510044 ?
Unique (%)77.8%

allergens
Categorical

HIGH CARDINALITY
MISSING

Distinct6381
Distinct (%)3.7%
Missing1350981
Missing (%)88.6%
Memory size11.6 MiB
en:milk
37067 
en:gluten
23702 
en:gluten,en:milk
11263 
en:nuts
 
7495
en:eggs,en:gluten,en:milk
 
7188
Other values (6376)
86883 
ValueCountFrequency (%) 
en:milk370672.4%
 
en:gluten237021.6%
 
en:gluten,en:milk112630.7%
 
en:nuts74950.5%
 
en:eggs,en:gluten,en:milk71880.5%
 
en:soybeans56530.4%
 
en:gluten,en:soybeans41730.3%
 
en:sulphur-dioxide-and-sulphites34990.2%
 
en:gluten,en:milk,en:soybeans33180.2%
 
en:milk,en:soybeans32670.2%
 
Other values (6371)669734.4%
 
(Missing)135098188.6%
 
2020-12-04T09:39:08.735192image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4924 ?
Unique (%)2.8%

allergens_en
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

traces
Categorical

HIGH CARDINALITY
MISSING

Distinct10115
Distinct (%)11.8%
Missing1439063
Missing (%)94.4%
Memory size11.6 MiB
en:nuts
8099 
en:milk
 
4296
en:gluten
 
2816
en:soybeans
 
2751
en:nuts,en:peanuts
 
2162
Other values (10110)
65392 
ValueCountFrequency (%) 
en:nuts80990.5%
 
en:milk42960.3%
 
en:gluten28160.2%
 
en:soybeans27510.2%
 
en:nuts,en:peanuts21620.1%
 
en:milk,en:nuts21340.1%
 
en:nuts,en:soybeans20530.1%
 
en:eggs19520.1%
 
en:gluten,en:nuts17270.1%
 
en:sesame-seeds12350.1%
 
Other values (10105)562913.7%
 
(Missing)143906394.4%
 
2020-12-04T09:39:08.925160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7808 ?
Unique (%)9.1%

traces_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct10210
Distinct (%)9.5%
Missing1417076
Missing (%)92.9%
Memory size11.6 MiB
en:nuts
10877 
en:milk
 
5116
en:soybeans
 
3814
en:gluten
 
3424
en:nuts,en:peanuts
 
2798
Other values (10205)
81474 
ValueCountFrequency (%) 
en:nuts108770.7%
 
en:milk51160.3%
 
en:soybeans38140.3%
 
en:gluten34240.2%
 
en:nuts,en:peanuts27980.2%
 
en:milk,en:nuts27520.2%
 
en:nuts,en:soybeans26410.2%
 
en:eggs24820.2%
 
en:gluten,en:nuts23040.2%
 
en:sesame-seeds16120.1%
 
Other values (10200)696834.6%
 
(Missing)141707692.9%
 
2020-12-04T09:39:09.113143image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7502 ?
Unique (%)7.0%

traces_en
Categorical

HIGH CARDINALITY
MISSING

Distinct10210
Distinct (%)9.5%
Missing1417076
Missing (%)92.9%
Memory size11.6 MiB
Nuts
10877 
Milk
 
5116
Soybeans
 
3814
Gluten
 
3424
Nuts,Peanuts
 
2798
Other values (10205)
81474 
ValueCountFrequency (%) 
Nuts108770.7%
 
Milk51160.3%
 
Soybeans38140.3%
 
Gluten34240.2%
 
Nuts,Peanuts27980.2%
 
Milk,Nuts27520.2%
 
Nuts,Soybeans26410.2%
 
Eggs24820.2%
 
Gluten,Nuts23040.2%
 
Sesame seeds16120.1%
 
Other values (10200)696834.6%
 
(Missing)141707692.9%
 
2020-12-04T09:39:09.290216image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7502 ?
Unique (%)7.0%

serving_size
Categorical

HIGH CARDINALITY
MISSING

Distinct45137
Distinct (%)10.1%
Missing1078152
Missing (%)70.7%
Memory size11.6 MiB
1 ONZ (28 g)
 
19888
100g
 
16993
8 OZA (240 ml)
 
8555
2 ONZ (56 g)
 
5702
30 g
 
5068
Other values (45132)
390221 
ValueCountFrequency (%) 
1 ONZ (28 g)198881.3%
 
100g169931.1%
 
8 OZA (240 ml)85550.6%
 
2 ONZ (56 g)57020.4%
 
30 g50680.3%
 
1 Tbsp (15 ml)47750.3%
 
2 Tbsp (30 g)44850.3%
 
100 g38830.3%
 
1 cup (240 ml)34880.2%
 
30g32820.2%
 
Other values (45127)37030824.3%
 
(Missing)107815270.7%
 
2020-12-04T09:39:09.557528image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique26577 ?
Unique (%)6.0%

serving_quantity
Real number (ℝ≥0)

MISSING
SKEWED

Distinct2181
Distinct (%)0.5%
Missing1077360
Missing (%)70.7%
Infinite0
Infinite (%)0.0%
Mean2.48448995e+16
Minimum0
Maximum1.111111111e+22
Zeros4869
Zeros (%)0.3%
Memory size11.6 MiB
2020-12-04T09:39:09.711819image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q128
median50
Q3113
95-th percentile296
Maximum1.111111111e+22
Range1.111111111e+22
Interquartile range (IQR)85

Descriptive statistics

Standard deviation1.661488606e+19
Coefficient of variation (CV)668.7443458
Kurtosis447219
Mean2.48448995e+16
Median Absolute Deviation (MAD)35
Skewness668.7443458
Sum1.111111111e+22
Variance2.760544389e+38
MonotocityNot monotonic
2020-12-04T09:39:09.853672image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
28366422.4%
 
30303542.0%
 
100276871.8%
 
240150601.0%
 
15139610.9%
 
40128210.8%
 
5693720.6%
 
8587060.6%
 
5076680.5%
 
12576180.5%
 
Other values (2171)27733018.2%
 
(Missing)107736070.7%
 
ValueCountFrequency (%) 
048690.3%
 
1e-062< 0.1%
 
2e-061< 0.1%
 
3e-061< 0.1%
 
2e-051< 0.1%
 
ValueCountFrequency (%) 
1.111111111e+221< 0.1%
 
6805878051< 0.1%
 
29757241< 0.1%
 
10000001< 0.1%
 
9779971< 0.1%
 

no_nutriments
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

additives_n
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)< 0.1%
Missing868794
Missing (%)57.0%
Infinite0
Infinite (%)0.0%
Mean2.05116616
Minimum0
Maximum49
Zeros274699
Zeros (%)18.0%
Memory size11.6 MiB
2020-12-04T09:39:09.995033image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile8
Maximum49
Range49
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.923523006
Coefficient of variation (CV)1.425297991
Kurtosis8.457545532
Mean2.05116616
Median Absolute Deviation (MAD)1
Skewness2.381634905
Sum1345124
Variance8.546986768
MonotocityNot monotonic
2020-12-04T09:39:10.139337image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%) 
027469918.0%
 
11147307.5%
 
2736124.8%
 
3520503.4%
 
4396472.6%
 
5283651.9%
 
6199191.3%
 
7149221.0%
 
8111490.7%
 
976090.5%
 
Other values (30)190831.3%
 
(Missing)86879457.0%
 
ValueCountFrequency (%) 
027469918.0%
 
11147307.5%
 
2736124.8%
 
3520503.4%
 
4396472.6%
 
ValueCountFrequency (%) 
491< 0.1%
 
411< 0.1%
 
391< 0.1%
 
381< 0.1%
 
371< 0.1%
 

additives
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

additives_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct89363
Distinct (%)23.4%
Missing1143493
Missing (%)75.0%
Memory size11.6 MiB
en:e330
 
24297
en:e322,en:e322i
 
17024
en:e440
 
5893
en:e415
 
4901
en:e300
 
3723
Other values (89358)
325248 
ValueCountFrequency (%) 
en:e330242971.6%
 
en:e322,en:e322i170241.1%
 
en:e44058930.4%
 
en:e41549010.3%
 
en:e30037230.2%
 
en:e14xx34180.2%
 
en:e500,en:e500ii31130.2%
 
en:e330,en:e44030560.2%
 
en:e160b29770.2%
 
en:e322,en:e322i,en:e500,en:e500ii25510.2%
 
Other values (89353)31013320.3%
 
(Missing)114349375.0%
 
2020-12-04T09:39:10.668076image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique63130 ?
Unique (%)16.6%

additives_en
Categorical

HIGH CARDINALITY
MISSING

Distinct89363
Distinct (%)23.4%
Missing1143493
Missing (%)75.0%
Memory size11.6 MiB
E330 - Citric acid
 
24297
E322 - Lecithins,E322i - Lecithin
 
17024
E440 - Pectins
 
5893
E415 - Xanthan gum
 
4901
E300 - Ascorbic acid
 
3723
Other values (89358)
325248 
ValueCountFrequency (%) 
E330 - Citric acid242971.6%
 
E322 - Lecithins,E322i - Lecithin170241.1%
 
E440 - Pectins58930.4%
 
E415 - Xanthan gum49010.3%
 
E300 - Ascorbic acid37230.2%
 
E14XX - Modified Starch34180.2%
 
E500 - Sodium carbonates,E500ii - Sodium hydrogen carbonate31130.2%
 
E330 - Citric acid,E440 - Pectins30560.2%
 
E160b - Annatto29770.2%
 
E322 - Lecithins,E322i - Lecithin,E500 - Sodium carbonates,E500ii - Sodium hydrogen carbonate25510.2%
 
Other values (89353)31013320.3%
 
(Missing)114349375.0%
 
2020-12-04T09:39:11.150684image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique63130 ?
Unique (%)16.6%

ingredients_from_palm_oil_n
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing868794
Missing (%)57.0%
Memory size11.6 MiB
0
642332 
1
 
13285
2
 
167
3
 
1
ValueCountFrequency (%) 
064233242.1%
 
1132850.9%
 
2167< 0.1%
 
31< 0.1%
 
(Missing)86879457.0%
 
2020-12-04T09:39:11.294524image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%

ingredients_from_palm_oil
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

ingredients_from_palm_oil_tags
Categorical

MISSING

Distinct16
Distinct (%)0.1%
Missing1511126
Missing (%)99.1%
Memory size11.6 MiB
huile-de-palme
12742 
e304-palmitate-d-ascorbyle
 
450
huile-de-palme,e304-palmitate-d-ascorbyle
 
121
oleine-de-palme
 
73
huile-de-palme,stearine-de-palme
 
18
Other values (11)
 
49
ValueCountFrequency (%) 
huile-de-palme127420.8%
 
e304-palmitate-d-ascorbyle450< 0.1%
 
huile-de-palme,e304-palmitate-d-ascorbyle121< 0.1%
 
oleine-de-palme73< 0.1%
 
huile-de-palme,stearine-de-palme18< 0.1%
 
huile-de-palme,oleine-de-palme11< 0.1%
 
mono-et-diglycerides-d-acides-gras-de-palme10< 0.1%
 
stearine-de-palme8< 0.1%
 
e304-palmitate-d-ascorbyle,huile-de-palme8< 0.1%
 
stearine-de-palme,huile-de-palme3< 0.1%
 
Other values (6)9< 0.1%
 
(Missing)151112699.1%
 
2020-12-04T09:39:11.434926image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%

ingredients_that_may_be_from_palm_oil_n
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing868794
Missing (%)57.0%
Infinite0
Infinite (%)0.0%
Mean0.06967527467
Minimum0
Maximum6
Zeros617066
Zeros (%)40.5%
Memory size11.6 MiB
2020-12-04T09:39:11.551946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3020562275
Coefficient of variation (CV)4.335199666
Kurtosis37.18008495
Mean0.06967527467
Median Absolute Deviation (MAD)0
Skewness5.368633489
Sum45692
Variance0.09123796456
MonotocityNot monotonic
2020-12-04T09:39:11.662554image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
061706640.5%
 
1331412.2%
 
244470.3%
 
38950.1%
 
4210< 0.1%
 
524< 0.1%
 
62< 0.1%
 
(Missing)86879457.0%
 
ValueCountFrequency (%) 
061706640.5%
 
1331412.2%
 
244470.3%
 
38950.1%
 
4210< 0.1%
 
ValueCountFrequency (%) 
62< 0.1%
 
524< 0.1%
 
4210< 0.1%
 
38950.1%
 
244470.3%
 

ingredients_that_may_be_from_palm_oil
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

ingredients_that_may_be_from_palm_oil_tags
Categorical

HIGH CARDINALITY
MISSING

Distinct328
Distinct (%)0.8%
Missing1485860
Missing (%)97.5%
Memory size11.6 MiB
e160a-beta-carotene
10409 
e471-mono-et-diglycerides-d-acides-gras-alimentaires
8908 
huile-vegetale
6999 
e433-monooleate-de-polyoxyethylene-de-sorbitane
5078 
huile-vegetale,e471-mono-et-diglycerides-d-acides-gras-alimentaires
1423 
Other values (323)
5902 
ValueCountFrequency (%) 
e160a-beta-carotene104090.7%
 
e471-mono-et-diglycerides-d-acides-gras-alimentaires89080.6%
 
huile-vegetale69990.5%
 
e433-monooleate-de-polyoxyethylene-de-sorbitane50780.3%
 
huile-vegetale,e471-mono-et-diglycerides-d-acides-gras-alimentaires14230.1%
 
e471-mono-et-diglycerides-d-acides-gras-alimentaires,e160a-beta-carotene7670.1%
 
e472e-ester-monoacethyltartrique-de-mono-et-diglycerides-d-acides-gras682< 0.1%
 
e471-mono-et-diglycerides-d-acides-gras-alimentaires,e481-stearoyl-2-lactylate-de-sodium499< 0.1%
 
e471-mono-et-diglycerides-d-acides-gras-alimentaires,e472e-ester-monoacethyltartrique-de-mono-et-diglycerides-d-acides-gras427< 0.1%
 
e472b-ester-diacetyl-lactique-de-mono-et-diglycerides-d-acides-gras301< 0.1%
 
Other values (318)32260.2%
 
(Missing)148586097.5%
 
2020-12-04T09:39:11.852026image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique152 ?
Unique (%)0.4%

nutriscore_score
Real number (ℝ)

MISSING
ZEROS

Distinct55
Distinct (%)< 0.1%
Missing914694
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean9.148104971
Minimum-15
Maximum40
Zeros30887
Zeros (%)2.0%
Memory size11.6 MiB
2020-12-04T09:39:12.085645image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-15
5-th percentile-4
Q11
median10
Q316
95-th percentile24
Maximum40
Range55
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.907433701
Coefficient of variation (CV)0.9736916804
Kurtosis-0.955505093
Mean9.148104971
Median Absolute Deviation (MAD)7
Skewness0.08645060498
Sum5579292
Variance79.34237514
MonotocityNot monotonic
2020-12-04T09:39:12.267179image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
14316842.1%
 
0308872.0%
 
13269021.8%
 
11267711.8%
 
2259841.7%
 
15253921.7%
 
1250491.6%
 
3248171.6%
 
12246691.6%
 
16235311.5%
 
Other values (45)34419922.6%
 
(Missing)91469460.0%
 
ValueCountFrequency (%) 
-155< 0.1%
 
-1472< 0.1%
 
-13149< 0.1%
 
-12244< 0.1%
 
-11328< 0.1%
 
ValueCountFrequency (%) 
405< 0.1%
 
391< 0.1%
 
379< 0.1%
 
3627< 0.1%
 
3537< 0.1%
 

nutriscore_grade
Categorical

MISSING

Distinct5
Distinct (%)< 0.1%
Missing914694
Missing (%)60.0%
Memory size11.6 MiB
d
188861 
c
128403 
e
114772 
a
98997 
b
78852 
ValueCountFrequency (%) 
d18886112.4%
 
c1284038.4%
 
e1147727.5%
 
a989976.5%
 
b788525.2%
 
(Missing)91469460.0%
 
2020-12-04T09:39:12.443260image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

nova_group
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing951023
Missing (%)62.4%
Memory size11.6 MiB
4
382620 
3
118781 
1
61221 
2
 
10934
ValueCountFrequency (%) 
438262025.1%
 
31187817.8%
 
1612214.0%
 
2109340.7%
 
(Missing)95102362.4%
 
2020-12-04T09:39:12.598013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

pnns_groups_1
Categorical

MISSING

Distinct14
Distinct (%)< 0.1%
Missing15376
Missing (%)1.0%
Memory size11.6 MiB
unknown
896010 
Sugary snacks
129707 
Milk and dairy products
 
79577
Fish Meat Eggs
 
78249
Cereals and potatoes
 
72143
Other values (9)
253517 
ValueCountFrequency (%) 
unknown89601058.8%
 
Sugary snacks1297078.5%
 
Milk and dairy products795775.2%
 
Fish Meat Eggs782495.1%
 
Cereals and potatoes721434.7%
 
Fat and sauces614474.0%
 
Beverages603254.0%
 
Composite foods490063.2%
 
Fruits and vegetables419792.8%
 
Salty snacks289161.9%
 
Other values (4)118440.8%
 
(Missing)153761.0%
 
2020-12-04T09:39:12.744363image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

pnns_groups_2
Categorical

Distinct46
Distinct (%)< 0.1%
Missing881
Missing (%)0.1%
Memory size11.6 MiB
unknown
896010 
Sweets
 
59942
Biscuits and cakes
 
56931
Dressings and sauces
 
44119
One-dish meals
 
38730
Other values (41)
427966 
ValueCountFrequency (%) 
unknown89601058.8%
 
Sweets599423.9%
 
Biscuits and cakes569313.7%
 
Dressings and sauces441192.9%
 
One-dish meals387302.5%
 
Cheese383632.5%
 
Cereals349132.3%
 
Processed meat297211.9%
 
Milk and yogurt296451.9%
 
Meat234851.5%
 
Other values (36)27183917.8%
 
2020-12-04T09:39:12.892637image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

states
Categorical

HIGH CARDINALITY

Distinct2877
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 MiB
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded
207165 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-completed, en:brands-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-uploaded
141633 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-uploaded
128412 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded
 
85448
en:to-be-completed, en:nutrition-facts-to-be-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded
 
57831
Other values (2872)
904090 
ValueCountFrequency (%) 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded20716513.6%
 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-completed, en:brands-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-uploaded1416339.3%
 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-uploaded1284128.4%
 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded854485.6%
 
en:to-be-completed, en:nutrition-facts-to-be-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded578313.8%
 
en:to-be-checked, en:complete, en:nutrition-facts-completed, en:ingredients-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-completed, en:categories-completed, en:brands-completed, en:packaging-completed, en:quantity-completed, en:product-name-completed, en:photos-validated, en:photos-uploaded500383.3%
 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-completed, en:brands-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded382512.5%
 
en:to-be-checked, en:complete, en:nutrition-facts-completed, en:ingredients-completed, en:expiration-date-completed, en:packaging-code-to-be-completed, en:characteristics-completed, en:categories-completed, en:brands-completed, en:packaging-completed, en:quantity-completed, en:product-name-completed, en:photos-validated, en:photos-uploaded370452.4%
 
en:to-be-completed, en:nutrition-facts-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-completed, en:photos-to-be-validated, en:photos-uploaded343112.3%
 
en:to-be-completed, en:nutrition-facts-to-be-completed, en:ingredients-to-be-completed, en:expiration-date-to-be-completed, en:packaging-code-to-be-completed, en:characteristics-to-be-completed, en:categories-to-be-completed, en:brands-to-be-completed, en:packaging-to-be-completed, en:quantity-to-be-completed, en:product-name-to-be-completed, en:photos-to-be-validated, en:photos-uploaded294441.9%
 
Other values (2867)71500146.9%
 
2020-12-04T09:39:13.099964image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique765 ?
Unique (%)0.1%

states_tags
Categorical

HIGH CARDINALITY

Distinct2877
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 MiB
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded
207165 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-completed,en:brands-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-uploaded
141633 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-uploaded
128412 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded
 
85448
en:to-be-completed,en:nutrition-facts-to-be-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded
 
57831
Other values (2872)
904090 
ValueCountFrequency (%) 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded20716513.6%
 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-completed,en:brands-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-uploaded1416339.3%
 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-uploaded1284128.4%
 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded854485.6%
 
en:to-be-completed,en:nutrition-facts-to-be-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded578313.8%
 
en:to-be-checked,en:complete,en:nutrition-facts-completed,en:ingredients-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-completed,en:categories-completed,en:brands-completed,en:packaging-completed,en:quantity-completed,en:product-name-completed,en:photos-validated,en:photos-uploaded500383.3%
 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-completed,en:brands-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded382512.5%
 
en:to-be-checked,en:complete,en:nutrition-facts-completed,en:ingredients-completed,en:expiration-date-completed,en:packaging-code-to-be-completed,en:characteristics-completed,en:categories-completed,en:brands-completed,en:packaging-completed,en:quantity-completed,en:product-name-completed,en:photos-validated,en:photos-uploaded370452.4%
 
en:to-be-completed,en:nutrition-facts-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-completed,en:photos-to-be-validated,en:photos-uploaded343112.3%
 
en:to-be-completed,en:nutrition-facts-to-be-completed,en:ingredients-to-be-completed,en:expiration-date-to-be-completed,en:packaging-code-to-be-completed,en:characteristics-to-be-completed,en:categories-to-be-completed,en:brands-to-be-completed,en:packaging-to-be-completed,en:quantity-to-be-completed,en:product-name-to-be-completed,en:photos-to-be-validated,en:photos-uploaded294441.9%
 
Other values (2867)71500146.9%
 
2020-12-04T09:39:13.327135image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique765 ?
Unique (%)0.1%

states_en
Categorical

HIGH CARDINALITY

Distinct2877
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 MiB
To be completed,Nutrition facts completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded
207165 
To be completed,Nutrition facts completed,Ingredients completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories completed,Brands completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be uploaded
141633 
To be completed,Nutrition facts completed,Ingredients completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be uploaded
128412 
To be completed,Nutrition facts completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded
 
85448
To be completed,Nutrition facts to be completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded
 
57831
Other values (2872)
904090 
ValueCountFrequency (%) 
To be completed,Nutrition facts completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded20716513.6%
 
To be completed,Nutrition facts completed,Ingredients completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories completed,Brands completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be uploaded1416339.3%
 
To be completed,Nutrition facts completed,Ingredients completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be uploaded1284128.4%
 
To be completed,Nutrition facts completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded854485.6%
 
To be completed,Nutrition facts to be completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded578313.8%
 
To be checked,Complete,Nutrition facts completed,Ingredients completed,Expiration date to be completed,Packaging code to be completed,Characteristics completed,Categories completed,Brands completed,Packaging completed,Quantity completed,Product name completed,Photos validated,Photos uploaded500383.3%
 
To be completed,Nutrition facts completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories completed,Brands completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded382512.5%
 
To be checked,Complete,Nutrition facts completed,Ingredients completed,Expiration date completed,Packaging code to be completed,Characteristics completed,Categories completed,Brands completed,Packaging completed,Quantity completed,Product name completed,Photos validated,Photos uploaded370452.4%
 
To be completed,Nutrition facts completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name completed,Photos to be validated,Photos uploaded343112.3%
 
To be completed,Nutrition facts to be completed,Ingredients to be completed,Expiration date to be completed,Packaging code to be completed,Characteristics to be completed,Categories to be completed,Brands to be completed,Packaging to be completed,Quantity to be completed,Product name to be completed,Photos to be validated,Photos uploaded294441.9%
 
Other values (2867)71500146.9%
 
2020-12-04T09:39:13.551846image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique765 ?
Unique (%)0.1%

brand_owner
Categorical

HIGH CARDINALITY
MISSING

Distinct25553
Distinct (%)8.8%
Missing1235298
Missing (%)81.0%
Memory size11.6 MiB
Wal-Mart Stores, Inc.
 
5389
Target Stores
 
4723
Topco Associates, Inc.
 
4627
Meijer, Inc.
 
4275
Safeway, Inc.
 
4035
Other values (25548)
266232 
ValueCountFrequency (%) 
Wal-Mart Stores, Inc.53890.4%
 
Target Stores47230.3%
 
Topco Associates, Inc.46270.3%
 
Meijer, Inc.42750.3%
 
Safeway, Inc.40350.3%
 
The Kroger Co.38810.3%
 
Hy-Vee, Inc.34590.2%
 
Supervalu, Inc.32800.2%
 
Wegmans Food Markets, Inc.28440.2%
 
Harris-Teeter Inc.27270.2%
 
Other values (25543)25004116.4%
 
(Missing)123529881.0%
 
2020-12-04T09:39:13.784477image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique11824 ?
Unique (%)4.1%

main_category
Categorical

HIGH CARDINALITY
MISSING

Distinct26724
Distinct (%)3.4%
Missing745084
Missing (%)48.9%
Memory size11.6 MiB
en:snacks
 
32865
en:sauces
 
15842
en:confectioneries
 
15050
en:biscuits
 
14089
en:cheeses
 
14050
Other values (26719)
687599 
ValueCountFrequency (%) 
en:snacks328652.2%
 
en:sauces158421.0%
 
en:confectioneries150501.0%
 
en:biscuits140890.9%
 
en:cheeses140500.9%
 
en:frozen-desserts92260.6%
 
en:beverages92250.6%
 
en:breads87800.6%
 
en:salted-snacks76860.5%
 
en:cereals-and-their-products74350.5%
 
Other values (26714)64524742.3%
 
(Missing)74508448.9%
 
2020-12-04T09:39:14.020541image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique16214 ?
Unique (%)2.1%

main_category_en
Categorical

HIGH CARDINALITY
MISSING

Distinct26723
Distinct (%)3.4%
Missing745084
Missing (%)48.9%
Memory size11.6 MiB
Snacks
 
32865
Sauces
 
15842
Confectioneries
 
15050
Biscuits
 
14089
Cheeses
 
14050
Other values (26718)
687599 
ValueCountFrequency (%) 
Snacks328652.2%
 
Sauces158421.0%
 
Confectioneries150501.0%
 
Biscuits140890.9%
 
Cheeses140500.9%
 
Frozen desserts92260.6%
 
Beverages92250.6%
 
Breads87800.6%
 
Salted-snacks76860.5%
 
Cereals and their products74350.5%
 
Other values (26713)64524742.3%
 
(Missing)74508448.9%
 
2020-12-04T09:39:14.254653image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique16213 ?
Unique (%)2.1%

image_url
URL

MISSING

Distinct1088117
Distinct (%)> 99.9%
Missing436306
Missing (%)28.6%
Memory size11.6 MiB
https://static.openfoodfacts.org/images/products/invalid/front_fr.3.400.jpg
 
49
https://static.openfoodfacts.org/images/products/invalid/front_en.3.400.jpg
 
26
https://static.openfoodfacts.org/images/products/invalid/front_fr.4.400.jpg
 
16
https://static.openfoodfacts.org/images/products/invalid/front_es.3.400.jpg
 
10
https://static.openfoodfacts.org/images/products/invalid/front_fr.5.400.jpg
 
8
Other values (1088112)
1088164 
(Missing)
436306 
ValueCountFrequency (%) 
https://static.openfoodfacts.org/images/products/invalid/front_fr.3.400.jpg49< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_en.3.400.jpg26< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.4.400.jpg16< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_es.3.400.jpg10< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.5.400.jpg8< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_es.4.400.jpg8< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_en.4.400.jpg7< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_de.3.400.jpg7< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.6.400.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.8.400.jpg4< 0.1%
 
Other values (1088107)108813371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
https108827371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
static.openfoodfacts.org108827371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
/images/products/invalid/front_fr.3.400.jpg49< 0.1%
 
/images/products/invalid/front_en.3.400.jpg26< 0.1%
 
/images/products/invalid/front_fr.4.400.jpg16< 0.1%
 
/images/products/invalid/front_es.3.400.jpg10< 0.1%
 
/images/products/invalid/front_fr.5.400.jpg8< 0.1%
 
/images/products/invalid/front_es.4.400.jpg8< 0.1%
 
/images/products/invalid/front_de.3.400.jpg7< 0.1%
 
/images/products/invalid/front_en.4.400.jpg7< 0.1%
 
/images/products/invalid/front_fr.6.400.jpg5< 0.1%
 
/images/products/invalid/front_fr.8.400.jpg4< 0.1%
 
Other values (1088107)108813371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
108827371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
108827371.4%
 
(Missing)43630628.6%
 

image_small_url
URL

MISSING

Distinct1088117
Distinct (%)> 99.9%
Missing436306
Missing (%)28.6%
Memory size11.6 MiB
https://static.openfoodfacts.org/images/products/invalid/front_fr.3.200.jpg
 
49
https://static.openfoodfacts.org/images/products/invalid/front_en.3.200.jpg
 
26
https://static.openfoodfacts.org/images/products/invalid/front_fr.4.200.jpg
 
16
https://static.openfoodfacts.org/images/products/invalid/front_es.3.200.jpg
 
10
https://static.openfoodfacts.org/images/products/invalid/front_es.4.200.jpg
 
8
Other values (1088112)
1088164 
(Missing)
436306 
ValueCountFrequency (%) 
https://static.openfoodfacts.org/images/products/invalid/front_fr.3.200.jpg49< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_en.3.200.jpg26< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.4.200.jpg16< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_es.3.200.jpg10< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_es.4.200.jpg8< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.5.200.jpg8< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_en.4.200.jpg7< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_de.3.200.jpg7< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.6.200.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/front_fr.8.200.jpg4< 0.1%
 
Other values (1088107)108813371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
https108827371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
static.openfoodfacts.org108827371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
/images/products/invalid/front_fr.3.200.jpg49< 0.1%
 
/images/products/invalid/front_en.3.200.jpg26< 0.1%
 
/images/products/invalid/front_fr.4.200.jpg16< 0.1%
 
/images/products/invalid/front_es.3.200.jpg10< 0.1%
 
/images/products/invalid/front_es.4.200.jpg8< 0.1%
 
/images/products/invalid/front_fr.5.200.jpg8< 0.1%
 
/images/products/invalid/front_de.3.200.jpg7< 0.1%
 
/images/products/invalid/front_en.4.200.jpg7< 0.1%
 
/images/products/invalid/front_fr.6.200.jpg5< 0.1%
 
/images/products/invalid/front_fr.8.200.jpg4< 0.1%
 
Other values (1088107)108813371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
108827371.4%
 
(Missing)43630628.6%
 
ValueCountFrequency (%) 
108827371.4%
 
(Missing)43630628.6%
 

image_ingredients_url
URL

MISSING

Distinct639708
Distinct (%)> 99.9%
Missing884840
Missing (%)58.0%
Memory size11.6 MiB
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.7.400.jpg
 
9
https://static.openfoodfacts.org/images/products/invalid/ingredients_en.5.400.jpg
 
5
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.25.400.jpg
 
3
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.10.400.jpg
 
3
https://static.openfoodfacts.org/images/products/invalid/ingredients_es.4.400.jpg
 
3
Other values (639703)
639716 
(Missing)
884840 
ValueCountFrequency (%) 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.7.400.jpg9< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_en.5.400.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.25.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.10.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_es.4.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.8.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.4.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.9.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/322/044/017/6203/ingredients_fr.6.400.jpg2< 0.1%
 
https://static.openfoodfacts.org/images/products/326/183/012/3377/ingredients_fr.7.400.jpg2< 0.1%
 
Other values (639698)63970342.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
https63973942.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
static.openfoodfacts.org63973942.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
/images/products/invalid/ingredients_fr.7.400.jpg9< 0.1%
 
/images/products/invalid/ingredients_en.5.400.jpg5< 0.1%
 
/images/products/invalid/ingredients_fr.10.400.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.25.400.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.4.400.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.9.400.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.8.400.jpg3< 0.1%
 
/images/products/invalid/ingredients_es.4.400.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.5.400.jpg2< 0.1%
 
/images/products/541/082/703/1715/ingredients_fr.4.400.jpg2< 0.1%
 
Other values (639698)63970342.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
63973942.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
63973942.0%
 
(Missing)88484058.0%
 

image_ingredients_small_url
URL

MISSING

Distinct639708
Distinct (%)> 99.9%
Missing884840
Missing (%)58.0%
Memory size11.6 MiB
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.7.200.jpg
 
9
https://static.openfoodfacts.org/images/products/invalid/ingredients_en.5.200.jpg
 
5
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.9.200.jpg
 
3
https://static.openfoodfacts.org/images/products/invalid/ingredients_es.4.200.jpg
 
3
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.8.200.jpg
 
3
Other values (639703)
639716 
(Missing)
884840 
ValueCountFrequency (%) 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.7.200.jpg9< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_en.5.200.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.9.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_es.4.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.8.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.10.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.25.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.4.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.5.200.jpg2< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/ingredients_fr.19.200.jpg2< 0.1%
 
Other values (639698)63970342.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
https63973942.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
static.openfoodfacts.org63973942.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
/images/products/invalid/ingredients_fr.7.200.jpg9< 0.1%
 
/images/products/invalid/ingredients_en.5.200.jpg5< 0.1%
 
/images/products/invalid/ingredients_es.4.200.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.10.200.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.25.200.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.9.200.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.8.200.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.4.200.jpg3< 0.1%
 
/images/products/invalid/ingredients_fr.19.200.jpg2< 0.1%
 
/images/products/invalid/ingredients_de.7.200.jpg2< 0.1%
 
Other values (639698)63970342.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
63973942.0%
 
(Missing)88484058.0%
 
ValueCountFrequency (%) 
63973942.0%
 
(Missing)88484058.0%
 

image_nutrition_url
URL

MISSING

Distinct656670
Distinct (%)> 99.9%
Missing867873
Missing (%)56.9%
Memory size11.6 MiB
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.4.400.jpg
 
7
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.5.400.jpg
 
6
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.11.400.jpg
 
5
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.10.400.jpg
 
5
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.3.400.jpg
 
4
Other values (656665)
656679 
(Missing)
867873 
ValueCountFrequency (%) 
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.4.400.jpg7< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.5.400.jpg6< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.11.400.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.10.400.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.3.400.jpg4< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.7.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.5.400.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_en.7.400.jpg2< 0.1%
 
https://static.openfoodfacts.org/images/products/345/468/100/6511/nutrition_fr.12.400.jpg2< 0.1%
 
https://static.openfoodfacts.org/images/products/221/024/803/0310/nutrition_fr.5.400.jpg2< 0.1%
 
Other values (656660)65666743.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
https65670643.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
static.openfoodfacts.org65670643.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
/images/products/invalid/nutrition_es.4.400.jpg7< 0.1%
 
/images/products/invalid/nutrition_fr.5.400.jpg6< 0.1%
 
/images/products/invalid/nutrition_fr.11.400.jpg5< 0.1%
 
/images/products/invalid/nutrition_fr.10.400.jpg5< 0.1%
 
/images/products/invalid/nutrition_es.3.400.jpg4< 0.1%
 
/images/products/invalid/nutrition_fr.7.400.jpg3< 0.1%
 
/images/products/invalid/nutrition_es.5.400.jpg3< 0.1%
 
/images/products/345/468/100/6511/nutrition_fr.12.400.jpg2< 0.1%
 
/images/products/invalid/nutrition_en.7.400.jpg2< 0.1%
 
/images/products/invalid/nutrition_en.11.400.jpg2< 0.1%
 
Other values (656660)65666743.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
65670643.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
65670643.1%
 
(Missing)86787356.9%
 

image_nutrition_small_url
URL

MISSING

Distinct656670
Distinct (%)> 99.9%
Missing867873
Missing (%)56.9%
Memory size11.6 MiB
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.4.200.jpg
 
7
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.5.200.jpg
 
6
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.11.200.jpg
 
5
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.10.200.jpg
 
5
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.3.200.jpg
 
4
Other values (656665)
656679 
(Missing)
867873 
ValueCountFrequency (%) 
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.4.200.jpg7< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.5.200.jpg6< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.11.200.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.10.200.jpg5< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.3.200.jpg4< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_es.5.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.7.200.jpg3< 0.1%
 
https://static.openfoodfacts.org/images/products/322/044/017/6203/nutrition_fr.7.200.jpg2< 0.1%
 
https://static.openfoodfacts.org/images/products/376/022/843/1501/nutrition_fr.5.200.jpg2< 0.1%
 
https://static.openfoodfacts.org/images/products/invalid/nutrition_fr.13.200.jpg2< 0.1%
 
Other values (656660)65666743.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
https65670643.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
static.openfoodfacts.org65670643.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
/images/products/invalid/nutrition_es.4.200.jpg7< 0.1%
 
/images/products/invalid/nutrition_fr.5.200.jpg6< 0.1%
 
/images/products/invalid/nutrition_fr.10.200.jpg5< 0.1%
 
/images/products/invalid/nutrition_fr.11.200.jpg5< 0.1%
 
/images/products/invalid/nutrition_es.3.200.jpg4< 0.1%
 
/images/products/invalid/nutrition_es.5.200.jpg3< 0.1%
 
/images/products/invalid/nutrition_fr.7.200.jpg3< 0.1%
 
/images/products/322/044/017/6203/nutrition_fr.7.200.jpg2< 0.1%
 
/images/products/221/024/803/0310/nutrition_fr.5.200.jpg2< 0.1%
 
/images/products/invalid/nutrition_fr.22.200.jpg2< 0.1%
 
Other values (656660)65666743.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
65670643.1%
 
(Missing)86787356.9%
 
ValueCountFrequency (%) 
65670643.1%
 
(Missing)86787356.9%
 

energy-kj_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct4541
Distinct (%)4.1%
Missing1412889
Missing (%)92.7%
Infinite0
Infinite (%)0.0%
Mean5.967910188e+37
Minimum0
Maximum6.665558889e+42
Zeros821
Zeros (%)0.1%
Memory size11.6 MiB
2020-12-04T09:39:33.900273image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile103
Q1398
median974
Q31616
95-th percentile2380
Maximum6.665558889e+42
Range6.665558889e+42
Interquartile range (IQR)1218

Descriptive statistics

Standard deviation1.994478799e+40
Coefficient of variation (CV)334.2005386
Kurtosis111690
Mean5.967910188e+37
Median Absolute Deviation (MAD)603
Skewness334.2005386
Sum6.665558889e+42
Variance3.97794568e+80
MonotocityNot monotonic
2020-12-04T09:39:34.034687image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
08210.1%
 
3700452< 0.1%
 
1700263< 0.1%
 
190230< 0.1%
 
3404229< 0.1%
 
170225< 0.1%
 
180224< 0.1%
 
197208< 0.1%
 
200207< 0.1%
 
195206< 0.1%
 
Other values (4531)1086257.1%
 
(Missing)141288992.7%
 
ValueCountFrequency (%) 
08210.1%
 
0.0011< 0.1%
 
0.021< 0.1%
 
0.2251< 0.1%
 
0.31< 0.1%
 
ValueCountFrequency (%) 
6.665558889e+421< 0.1%
 
252001< 0.1%
 
218481< 0.1%
 
215571< 0.1%
 
209001< 0.1%
 

energy-kcal_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct12095
Distinct (%)1.0%
Missing372176
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean7553064.597
Minimum0
Maximum8.693855001e+12
Zeros35624
Zeros (%)2.3%
Memory size11.6 MiB
2020-12-04T09:39:34.185968image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q1101
median263
Q3400
95-th percentile583
Maximum8.693855001e+12
Range8.693855001e+12
Interquartile range (IQR)299

Descriptive statistics

Standard deviation8098610074
Coefficient of variation (CV)1072.228361
Kurtosis1152399.951
Mean7553064.597
Median Absolute Deviation (MAD)152
Skewness1073.498221
Sum8.704174301e+12
Variance6.558748513e+19
MonotocityNot monotonic
2020-12-04T09:39:34.323361image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0356242.3%
 
500116030.8%
 
400107870.7%
 
35784430.6%
 
37573150.5%
 
39372160.5%
 
33371260.5%
 
25070100.5%
 
169610.5%
 
4658570.4%
 
Other values (12085)104446168.5%
 
(Missing)37217624.4%
 
ValueCountFrequency (%) 
0356242.3%
 
1e-091< 0.1%
 
0.0002351< 0.1%
 
0.0012< 0.1%
 
0.0021141648581< 0.1%
 
ValueCountFrequency (%) 
8.693855001e+121< 0.1%
 
1e+101< 0.1%
 
13333331< 0.1%
 
6901641< 0.1%
 
1370001< 0.1%
 

energy_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct5809
Distinct (%)0.5%
Missing304182
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean5.461795538e+36
Minimum0
Maximum6.665558889e+42
Zeros36131
Zeros (%)2.4%
Memory size11.6 MiB
2020-12-04T09:39:34.472163image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50
Q1418
median1088
Q31674
95-th percentile2427
Maximum6.665558889e+42
Range6.665558889e+42
Interquartile range (IQR)1256

Descriptive statistics

Standard deviation6.03373183e+39
Coefficient of variation (CV)1104.715801
Kurtosis1220397
Mean5.461795538e+36
Median Absolute Deviation (MAD)632
Skewness1104.715801
Sum6.665558889e+42
Variance3.64059198e+79
MonotocityNot monotonic
2020-12-04T09:39:34.613488image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0361312.4%
 
2092113460.7%
 
1674104730.7%
 
149485800.6%
 
164472950.5%
 
156971860.5%
 
139369610.5%
 
469380.5%
 
104668820.5%
 
19258330.4%
 
Other values (5799)111277273.0%
 
(Missing)30418220.0%
 
ValueCountFrequency (%) 
0361312.4%
 
0.0009751< 0.1%
 
0.0011< 0.1%
 
0.021< 0.1%
 
0.09281< 0.1%
 
ValueCountFrequency (%) 
6.665558889e+421< 0.1%
 
3.637508932e+131< 0.1%
 
4.184e+101< 0.1%
 
55786651< 0.1%
 
28876461< 0.1%
 

energy-from-fat_100g
Real number (ℝ≥0)

MISSING

Distinct243
Distinct (%)25.1%
Missing1523610
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean349.5579979
Minimum0
Maximum3830
Zeros199
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:34.778657image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q142
median167
Q3420
95-th percentile1350
Maximum3830
Range3830
Interquartile range (IQR)378

Descriptive statistics

Standard deviation515.1348493
Coefficient of variation (CV)1.473674905
Kurtosis12.48962129
Mean349.5579979
Median Absolute Deviation (MAD)167
Skewness3.049156658
Sum338721.7
Variance265363.913
MonotocityNot monotonic
2020-12-04T09:39:34.933905image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0199< 0.1%
 
4263< 0.1%
 
33541< 0.1%
 
25140< 0.1%
 
10528< 0.1%
 
16724< 0.1%
 
6324< 0.1%
 
20923< 0.1%
 
18822< 0.1%
 
41821< 0.1%
 
Other values (233)484< 0.1%
 
(Missing)152361099.9%
 
ValueCountFrequency (%) 
0199< 0.1%
 
41< 0.1%
 
82< 0.1%
 
11.31< 0.1%
 
131< 0.1%
 
ValueCountFrequency (%) 
38301< 0.1%
 
37401< 0.1%
 
35901< 0.1%
 
33503< 0.1%
 
29903< 0.1%
 

fat_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct10607
Distinct (%)0.9%
Missing313681
Missing (%)20.6%
Infinite0
Infinite (%)0.0%
Mean13.72029831
Minimum0
Maximum100000.1111
Zeros195507
Zeros (%)12.8%
Memory size11.6 MiB
2020-12-04T09:39:35.108993image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6666666766
median6.98
Q321.43
95-th percentile46
Maximum100000.1111
Range100000.1111
Interquartile range (IQR)20.76333332

Descriptive statistics

Standard deviation92.76931655
Coefficient of variation (CV)6.761464983
Kurtosis1114410.428
Mean13.72029831
Median Absolute Deviation (MAD)6.98
Skewness1034.197371
Sum16613881.78
Variance8606.146093
MonotocityNot monotonic
2020-12-04T09:39:35.267615image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
019550712.8%
 
0.5373512.4%
 
0.1201301.3%
 
1138980.9%
 
20133900.9%
 
25132940.9%
 
10126030.8%
 
0.2121290.8%
 
15114920.8%
 
12110820.7%
 
Other values (10597)87002257.1%
 
(Missing)31368120.6%
 
ValueCountFrequency (%) 
019550712.8%
 
1e-103< 0.1%
 
1e-091< 0.1%
 
1e-071< 0.1%
 
5e-071< 0.1%
 
ValueCountFrequency (%) 
100000.11111< 0.1%
 
58881< 0.1%
 
15001< 0.1%
 
14001< 0.1%
 
13001< 0.1%
 

saturated-fat_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct7962
Distinct (%)0.7%
Missing359896
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean116769976.3
Minimum0
Maximum1.360000002e+14
Zeros248203
Zeros (%)16.3%
Memory size11.6 MiB
2020-12-04T09:39:35.426900image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median1.9
Q37.2
95-th percentile20
Maximum1.360000002e+14
Range1.360000002e+14
Interquartile range (IQR)7.1

Descriptive statistics

Standard deviation1.260187133e+11
Coefficient of variation (CV)1079.204752
Kurtosis1164683
Mean116769976.3
Median Absolute Deviation (MAD)1.9
Skewness1079.2048
Sum1.360000063e+14
Variance1.58807161e+22
MonotocityNot monotonic
2020-12-04T09:39:35.609404image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
024820316.3%
 
0.1465063.1%
 
0.5222041.5%
 
0.2209351.4%
 
1205361.3%
 
0.3189171.2%
 
0.4159521.0%
 
2138670.9%
 
0.6116810.8%
 
0.8108850.7%
 
Other values (7952)73499748.2%
 
(Missing)35989623.6%
 
ValueCountFrequency (%) 
024820316.3%
 
1e-101< 0.1%
 
1e-092< 0.1%
 
1e-083< 0.1%
 
1e-073< 0.1%
 
ValueCountFrequency (%) 
1.360000002e+141< 0.1%
 
55551< 0.1%
 
20001< 0.1%
 
17801< 0.1%
 
14001< 0.1%
 

-butyric-acid_100g
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)100.0%
Missing1524574
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.0149240039
Minimum0
Maximum0.066
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:35.756220image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.9e-09
Q11.95e-08
median0.0018
Q30.00682
95-th percentile0.054164
Maximum0.066
Range0.066
Interquartile range (IQR)0.0068199805

Descriptive statistics

Standard deviation0.02868851224
Coefficient of variation (CV)1.92230667
Kurtosis4.804504618
Mean0.0149240039
Median Absolute Deviation (MAD)0.0018
Skewness2.184742715
Sum0.0746200195
Variance0.0008230307345
MonotocityNot monotonic
2020-12-04T09:39:35.863356image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
0.006821< 0.1%
 
0.00181< 0.1%
 
0.0661< 0.1%
 
1.95e-081< 0.1%
 
01< 0.1%
 
(Missing)1524574> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
1.95e-081< 0.1%
 
0.00181< 0.1%
 
0.006821< 0.1%
 
0.0661< 0.1%
 
ValueCountFrequency (%) 
0.0661< 0.1%
 
0.006821< 0.1%
 
0.00181< 0.1%
 
1.95e-081< 0.1%
 
01< 0.1%
 

-caproic-acid_100g
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing1524578
Missing (%)> 99.9%
Memory size11.6 MiB
48
1 
ValueCountFrequency (%) 
481< 0.1%
 
(Missing)1524578> 99.9%
 
2020-12-04T09:39:36.002235image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%

-caprylic-acid_100g
Categorical

MISSING

Distinct2
Distinct (%)100.0%
Missing1524577
Missing (%)> 99.9%
Memory size11.6 MiB
7.4
1 
97
1 
ValueCountFrequency (%) 
7.41< 0.1%
 
971< 0.1%
 
(Missing)1524577> 99.9%
 
2020-12-04T09:39:36.129708image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)100.0%

-capric-acid_100g
Categorical

MISSING

Distinct4
Distinct (%)100.0%
Missing1524575
Missing (%)> 99.9%
Memory size11.6 MiB
0.82
1 
6.2
1 
5.88
1 
0
1 
ValueCountFrequency (%) 
0.821< 0.1%
 
6.21< 0.1%
 
5.881< 0.1%
 
01< 0.1%
 
(Missing)1524575> 99.9%
 
2020-12-04T09:39:36.263133image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)100.0%

-lauric-acid_100g
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)88.9%
Missing1524570
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean37.39385889
Minimum0
Maximum50
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:36.373270image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.017892
Q145
median48
Q349
95-th percentile49.72
Maximum50
Range50
Interquartile range (IQR)4

Descriptive statistics

Standard deviation21.24625219
Coefficient of variation (CV)0.5681749042
Kurtosis0.6930477492
Mean37.39385889
Median Absolute Deviation (MAD)1.8
Skewness-1.596220059
Sum336.54473
Variance451.4032322
MonotocityNot monotonic
2020-12-04T09:39:36.487821image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
492< 0.1%
 
46.21< 0.1%
 
49.31< 0.1%
 
0.044731< 0.1%
 
501< 0.1%
 
481< 0.1%
 
451< 0.1%
 
01< 0.1%
 
(Missing)1524570> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.044731< 0.1%
 
451< 0.1%
 
46.21< 0.1%
 
481< 0.1%
 
ValueCountFrequency (%) 
501< 0.1%
 
49.31< 0.1%
 
492< 0.1%
 
481< 0.1%
 
46.21< 0.1%
 

-myristic-acid_100g
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing1524578
Missing (%)> 99.9%
Memory size11.6 MiB
18.9
1 
ValueCountFrequency (%) 
18.91< 0.1%
 
(Missing)1524578> 99.9%
 
2020-12-04T09:39:36.615789image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%

-palmitic-acid_100g
Categorical

MISSING

Distinct3
Distinct (%)100.0%
Missing1524576
Missing (%)> 99.9%
Memory size11.6 MiB
0.00518
1 
8.1
1 
0.002
1 
ValueCountFrequency (%) 
0.005181< 0.1%
 
8.11< 0.1%
 
0.0021< 0.1%
 
(Missing)1524576> 99.9%
 
2020-12-04T09:39:36.736813image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)100.0%

-stearic-acid_100g
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing1524578
Missing (%)> 99.9%
Memory size11.6 MiB
3
1 
ValueCountFrequency (%) 
31< 0.1%
 
(Missing)1524578> 99.9%
 
2020-12-04T09:39:36.857075image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%

-arachidic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct33
Distinct (%)70.2%
Missing1524532
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3.706336809
Minimum0
Maximum92.6
Zeros12
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:36.978099image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16e-05
median0.008
Q30.0887
95-th percentile16.3
Maximum92.6
Range92.6
Interquartile range (IQR)0.08864

Descriptive statistics

Standard deviation14.36146042
Coefficient of variation (CV)3.87483954
Kurtosis33.52221359
Mean3.706336809
Median Absolute Deviation (MAD)0.008
Skewness5.558850525
Sum174.19783
Variance206.2515453
MonotocityNot monotonic
2020-12-04T09:39:37.107059image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
012< 0.1%
 
0.0132< 0.1%
 
0.000122< 0.1%
 
0.0152< 0.1%
 
4.461< 0.1%
 
61< 0.1%
 
0.1671< 0.1%
 
0.2191< 0.1%
 
0.0041< 0.1%
 
0.00121< 0.1%
 
Other values (23)23< 0.1%
 
(Missing)1524532> 99.9%
 
ValueCountFrequency (%) 
012< 0.1%
 
0.000122< 0.1%
 
0.00031< 0.1%
 
0.00081< 0.1%
 
0.000841< 0.1%
 
ValueCountFrequency (%) 
92.61< 0.1%
 
31.21< 0.1%
 
191< 0.1%
 
101< 0.1%
 
81< 0.1%
 

-behenic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)89.5%
Missing1524560
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1.121852632
Minimum0
Maximum14.8
Zeros3
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:37.222627image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.000185
median0.008
Q30.1525
95-th percentile6.475
Maximum14.8
Range14.8
Interquartile range (IQR)0.152315

Descriptive statistics

Standard deviation3.543947627
Coefficient of variation (CV)3.159013516
Kurtosis13.84943628
Mean1.121852632
Median Absolute Deviation (MAD)0.008
Skewness3.661957428
Sum21.3152
Variance12.55956478
MonotocityNot monotonic
2020-12-04T09:39:37.328275image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
03< 0.1%
 
14.81< 0.1%
 
0.00081< 0.1%
 
0.000281< 0.1%
 
0.051< 0.1%
 
5.551< 0.1%
 
0.1621< 0.1%
 
0.1791< 0.1%
 
0.0081< 0.1%
 
0.1251< 0.1%
 
Other values (7)7< 0.1%
 
(Missing)1524560> 99.9%
 
ValueCountFrequency (%) 
03< 0.1%
 
3.6e-091< 0.1%
 
9e-051< 0.1%
 
0.000281< 0.1%
 
0.000531< 0.1%
 
ValueCountFrequency (%) 
14.81< 0.1%
 
5.551< 0.1%
 
0.1791< 0.1%
 
0.1771< 0.1%
 
0.1621< 0.1%
 

-lignoceric-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

-cerotic-acid_100g
Categorical

MISSING

Distinct2
Distinct (%)50.0%
Missing1524575
Missing (%)> 99.9%
Memory size11.6 MiB
0
3 
4
1 
ValueCountFrequency (%) 
03< 0.1%
 
41< 0.1%
 
(Missing)1524575> 99.9%
 
2020-12-04T09:39:37.463187image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)25.0%

-montanic-acid_100g
Categorical

MISSING

Distinct2
Distinct (%)100.0%
Missing1524577
Missing (%)> 99.9%
Memory size11.6 MiB
1
1 
61
1 
ValueCountFrequency (%) 
11< 0.1%
 
611< 0.1%
 
(Missing)1524577> 99.9%
 
2020-12-04T09:39:37.586228image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)100.0%

-melissic-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

monounsaturated-fat_100g
Real number (ℝ≥0)

MISSING

Distinct1417
Distinct (%)3.0%
Missing1477942
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean9.514764582
Minimum0
Maximum100
Zeros11712
Zeros (%)0.8%
Memory size11.6 MiB
2020-12-04T09:39:37.714692image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.53
Q310
95-th percentile53.33
Maximum100
Range100
Interquartile range (IQR)10

Descriptive statistics

Standard deviation15.86067854
Coefficient of variation (CV)1.666954385
Kurtosis6.933508936
Mean9.514764582
Median Absolute Deviation (MAD)3.53
Skewness2.665652367
Sum443740.0758
Variance251.5611239
MonotocityNot monotonic
2020-12-04T09:39:37.858535image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0117120.8%
 
7.1410430.1%
 
66.679580.1%
 
258520.1%
 
8.937710.1%
 
10736< 0.1%
 
6.67675< 0.1%
 
3.33620< 0.1%
 
5556< 0.1%
 
21.43553< 0.1%
 
Other values (1407)281611.8%
 
(Missing)147794296.9%
 
ValueCountFrequency (%) 
0117120.8%
 
5e-071< 0.1%
 
1.07e-051< 0.1%
 
1.6e-051< 0.1%
 
2.6e-051< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
891< 0.1%
 
86.672< 0.1%
 
85.712< 0.1%
 
83.571< 0.1%
 

polyunsaturated-fat_100g
Real number (ℝ≥0)

MISSING

Distinct1215
Distinct (%)2.6%
Missing1477914
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean5.834771978
Minimum0
Maximum100
Zeros12304
Zeros (%)0.8%
Memory size11.6 MiB
2020-12-04T09:39:38.005845image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.11
Q36.9
95-th percentile23.33
Maximum100
Range100
Interquartile range (IQR)6.9

Descriptive statistics

Standard deviation10.2022421
Coefficient of variation (CV)1.74852456
Kurtosis15.03127939
Mean5.834771978
Median Absolute Deviation (MAD)2.11
Skewness3.50266183
Sum272279.6343
Variance104.0857439
MonotocityNot monotonic
2020-12-04T09:39:38.142708image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0123040.8%
 
3.5710650.1%
 
1.799170.1%
 
0.898370.1%
 
108130.1%
 
7.14760< 0.1%
 
13.33681< 0.1%
 
14.29669< 0.1%
 
6.67615< 0.1%
 
3.33597< 0.1%
 
Other values (1205)274071.8%
 
(Missing)147791496.9%
 
ValueCountFrequency (%) 
0123040.8%
 
1.2e-061< 0.1%
 
8e-061< 0.1%
 
1.2e-051< 0.1%
 
3.53e-051< 0.1%
 
ValueCountFrequency (%) 
1004< 0.1%
 
981< 0.1%
 
973< 0.1%
 
951< 0.1%
 
86.671< 0.1%
 

omega-3-fat_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct464
Distinct (%)24.9%
Missing1522719
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean4.319621474
Minimum0
Maximum910
Zeros11
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:38.272660image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.037
Q10.4575
median1.73
Q33.5
95-th percentile12.22
Maximum910
Range910
Interquartile range (IQR)3.0425

Descriptive statistics

Standard deviation23.9363414
Coefficient of variation (CV)5.541305308
Kurtosis1127.7266
Mean4.319621474
Median Absolute Deviation (MAD)1.3835
Skewness31.09222314
Sum8034.495942
Variance572.9484398
MonotocityNot monotonic
2020-12-04T09:39:38.401620image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
266< 0.1%
 
1.853< 0.1%
 
153< 0.1%
 
2.345< 0.1%
 
1.539< 0.1%
 
0.835< 0.1%
 
333< 0.1%
 
0.132< 0.1%
 
0.329< 0.1%
 
0.627< 0.1%
 
Other values (454)14480.1%
 
(Missing)152271999.9%
 
ValueCountFrequency (%) 
011< 0.1%
 
8.1e-061< 0.1%
 
1.6e-053< 0.1%
 
2.1e-051< 0.1%
 
4e-051< 0.1%
 
ValueCountFrequency (%) 
9101< 0.1%
 
3501< 0.1%
 
1301< 0.1%
 
1201< 0.1%
 
1051< 0.1%
 

-alpha-linolenic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct209
Distinct (%)52.0%
Missing1524177
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean2.861753483
Minimum0
Maximum75
Zeros12
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:38.539013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0067315
Q10.07
median0.124
Q31.1225
95-th percentile17.99
Maximum75
Range75
Interquartile range (IQR)1.0525

Descriptive statistics

Standard deviation8.08152058
Coefficient of variation (CV)2.823975101
Kurtosis28.59640421
Mean2.861753483
Median Absolute Deviation (MAD)0.087
Skewness4.870245408
Sum1150.4249
Variance65.31097488
MonotocityNot monotonic
2020-12-04T09:39:39.062028image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.116< 0.1%
 
012< 0.1%
 
0.1211< 0.1%
 
0.0710< 0.1%
 
79< 0.1%
 
0.098< 0.1%
 
0.088< 0.1%
 
0.177< 0.1%
 
0.146< 0.1%
 
0.116< 0.1%
 
Other values (199)309< 0.1%
 
(Missing)1524177> 99.9%
 
ValueCountFrequency (%) 
012< 0.1%
 
0.000471< 0.1%
 
0.00122< 0.1%
 
0.001271< 0.1%
 
0.00212< 0.1%
 
ValueCountFrequency (%) 
751< 0.1%
 
531< 0.1%
 
473< 0.1%
 
461< 0.1%
 
371< 0.1%
 

-eicosapentaenoic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct68
Distinct (%)60.7%
Missing1524467
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1.541845025
Minimum0
Maximum85
Zeros5
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:39.204378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00053986
Q10.0774
median0.2773
Q30.6745
95-th percentile1.236
Maximum85
Range85
Interquartile range (IQR)0.5971

Descriptive statistics

Standard deviation8.79517899
Coefficient of variation (CV)5.704321023
Kurtosis77.36523603
Mean1.541845025
Median Absolute Deviation (MAD)0.25325
Skewness8.580667883
Sum172.6866428
Variance77.35517346
MonotocityNot monotonic
2020-12-04T09:39:39.326403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.59< 0.1%
 
0.29< 0.1%
 
0.77< 0.1%
 
05< 0.1%
 
0.65< 0.1%
 
15< 0.1%
 
0.44< 0.1%
 
0.094< 0.1%
 
0.024< 0.1%
 
1.22< 0.1%
 
Other values (58)58< 0.1%
 
(Missing)1524467> 99.9%
 
ValueCountFrequency (%) 
05< 0.1%
 
0.00033681< 0.1%
 
0.0007061< 0.1%
 
0.011< 0.1%
 
0.01051< 0.1%
 
ValueCountFrequency (%) 
851< 0.1%
 
39.641< 0.1%
 
4.91< 0.1%
 
1.61< 0.1%
 
1.51< 0.1%
 

-docosahexaenoic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct93
Distinct (%)60.8%
Missing1524426
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.4970466889
Minimum0
Maximum7.5
Zeros5
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:39.455849image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0007
Q10.064
median0.2
Q30.7
95-th percentile1.228
Maximum7.5
Range7.5
Interquartile range (IQR)0.636

Descriptive statistics

Standard deviation0.8899962839
Coefficient of variation (CV)1.790568781
Kurtosis40.01482203
Mean0.4970466889
Median Absolute Deviation (MAD)0.1989
Skewness5.711277896
Sum76.0481434
Variance0.7920933854
MonotocityNot monotonic
2020-12-04T09:39:39.588287image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.88< 0.1%
 
0.57< 0.1%
 
05< 0.1%
 
0.95< 0.1%
 
0.65< 0.1%
 
0.44< 0.1%
 
14< 0.1%
 
0.1264< 0.1%
 
0.0643< 0.1%
 
1.13< 0.1%
 
Other values (83)105< 0.1%
 
(Missing)1524426> 99.9%
 
ValueCountFrequency (%) 
05< 0.1%
 
0.0001241< 0.1%
 
0.00058941< 0.1%
 
0.00073< 0.1%
 
0.000791< 0.1%
 
ValueCountFrequency (%) 
7.51< 0.1%
 
6.71< 0.1%
 
3.21< 0.1%
 
1.72< 0.1%
 
1.41< 0.1%
 

omega-6-fat_100g
Real number (ℝ≥0)

MISSING

Distinct220
Distinct (%)49.4%
Missing1524134
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean13.88035395
Minimum0
Maximum71
Zeros6
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:39.733119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.122
Q11.2
median7.9
Q320.8
95-th percentile55.38
Maximum71
Range71
Interquartile range (IQR)19.6

Descriptive statistics

Standard deviation16.16832998
Coefficient of variation (CV)1.164835568
Kurtosis2.186882837
Mean13.88035395
Median Absolute Deviation (MAD)7.1
Skewness1.611099577
Sum6176.75751
Variance261.4148943
MonotocityNot monotonic
2020-12-04T09:39:39.863537image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1514< 0.1%
 
112< 0.1%
 
1.110< 0.1%
 
69< 0.1%
 
199< 0.1%
 
239< 0.1%
 
118< 0.1%
 
0.48< 0.1%
 
257< 0.1%
 
127< 0.1%
 
Other values (210)352< 0.1%
 
(Missing)1524134> 99.9%
 
ValueCountFrequency (%) 
06< 0.1%
 
7e-071< 0.1%
 
8.7e-051< 0.1%
 
0.0008541< 0.1%
 
0.0012< 0.1%
 
ValueCountFrequency (%) 
713< 0.1%
 
691< 0.1%
 
65.91< 0.1%
 
623< 0.1%
 
61.151< 0.1%
 

-linoleic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct148
Distinct (%)69.2%
Missing1524365
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3.819666248
Minimum0
Maximum36.9
Zeros2
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:40.005424image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.24815
Q10.448
median0.6265
Q33.6
95-th percentile22.35
Maximum36.9
Range36.9
Interquartile range (IQR)3.152

Descriptive statistics

Standard deviation6.968855467
Coefficient of variation (CV)1.824467117
Kurtosis7.22027795
Mean3.819666248
Median Absolute Deviation (MAD)0.2775
Skewness2.694841164
Sum817.408577
Variance48.56494653
MonotocityNot monotonic
2020-12-04T09:39:40.137855image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.59< 0.1%
 
0.496< 0.1%
 
235< 0.1%
 
3.54< 0.1%
 
74< 0.1%
 
3.64< 0.1%
 
4.24< 0.1%
 
0.4374< 0.1%
 
0.3543< 0.1%
 
0.63< 0.1%
 
Other values (138)168< 0.1%
 
(Missing)1524365> 99.9%
 
ValueCountFrequency (%) 
02< 0.1%
 
0.0005771< 0.1%
 
0.0211< 0.1%
 
0.041< 0.1%
 
0.081< 0.1%
 
ValueCountFrequency (%) 
36.91< 0.1%
 
36.11< 0.1%
 
35.11< 0.1%
 
253< 0.1%
 
235< 0.1%
 

-arachidonic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct35
Distinct (%)71.4%
Missing1524530
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean2.86009249
Minimum0
Maximum112
Zeros6
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:40.273760image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.00129
median0.035
Q30.064
95-th percentile4.4
Maximum112
Range112
Interquartile range (IQR)0.06271

Descriptive statistics

Standard deviation16.07893797
Coefficient of variation (CV)5.621824477
Kurtosis46.9268702
Mean2.86009249
Median Absolute Deviation (MAD)0.0335
Skewness6.796571962
Sum140.144532
Variance258.5322461
MonotocityNot monotonic
2020-12-04T09:39:40.381893image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%) 
06< 0.1%
 
0.0613< 0.1%
 
0.0593< 0.1%
 
0.00152< 0.1%
 
22< 0.1%
 
0.052< 0.1%
 
0.0642< 0.1%
 
0.002222< 0.1%
 
0.0441< 0.1%
 
0.0351< 0.1%
 
Other values (25)25< 0.1%
 
(Missing)1524530> 99.9%
 
ValueCountFrequency (%) 
06< 0.1%
 
1.2e-051< 0.1%
 
0.000121< 0.1%
 
0.000181< 0.1%
 
0.000731< 0.1%
 
ValueCountFrequency (%) 
1121< 0.1%
 
14.81< 0.1%
 
61< 0.1%
 
22< 0.1%
 
1.751< 0.1%
 

-gamma-linolenic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)100.0%
Missing1524574
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.859
Minimum0
Maximum2.8
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:40.479069image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.019
Q10.095
median0.6
Q30.8
95-th percentile2.4
Maximum2.8
Range2.8
Interquartile range (IQR)0.705

Descriptive statistics

Standard deviation1.135739847
Coefficient of variation (CV)1.32216513
Kurtosis3.331813228
Mean0.859
Median Absolute Deviation (MAD)0.505
Skewness1.767728259
Sum4.295
Variance1.289905
MonotocityNot monotonic
2020-12-04T09:39:40.562927image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
0.61< 0.1%
 
2.81< 0.1%
 
0.81< 0.1%
 
0.0951< 0.1%
 
01< 0.1%
 
(Missing)1524574> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.0951< 0.1%
 
0.61< 0.1%
 
0.81< 0.1%
 
2.81< 0.1%
 
ValueCountFrequency (%) 
2.81< 0.1%
 
0.81< 0.1%
 
0.61< 0.1%
 
0.0951< 0.1%
 
01< 0.1%
 

-dihomo-gamma-linolenic-acid_100g
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing1524578
Missing (%)> 99.9%
Memory size11.6 MiB
4.77
1 
ValueCountFrequency (%) 
4.771< 0.1%
 
(Missing)1524578> 99.9%
 
2020-12-04T09:39:40.674032image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%

omega-9-fat_100g
Real number (ℝ≥0)

MISSING

Distinct40
Distinct (%)76.9%
Missing1524527
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean33.94527308
Minimum0.0055
Maximum75
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:40.780670image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.0055
5-th percentile0.398515
Q111
median29
Q360.25
95-th percentile75
Maximum75
Range74.9945
Interquartile range (IQR)49.25

Descriptive statistics

Standard deviation25.38707577
Coefficient of variation (CV)0.7478825023
Kurtosis-1.292342716
Mean33.94527308
Median Absolute Deviation (MAD)23.5
Skewness0.2265362713
Sum1765.1542
Variance644.5036161
MonotocityNot monotonic
2020-12-04T09:39:40.900208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%) 
754< 0.1%
 
313< 0.1%
 
293< 0.1%
 
112< 0.1%
 
27.12< 0.1%
 
61.22< 0.1%
 
702< 0.1%
 
272< 0.1%
 
461< 0.1%
 
471< 0.1%
 
Other values (30)30< 0.1%
 
(Missing)1524527> 99.9%
 
ValueCountFrequency (%) 
0.00551< 0.1%
 
0.0221< 0.1%
 
0.06671< 0.1%
 
0.671< 0.1%
 
1.081< 0.1%
 
ValueCountFrequency (%) 
754< 0.1%
 
702< 0.1%
 
68.81< 0.1%
 
681< 0.1%
 
671< 0.1%
 

-oleic-acid_100g
Real number (ℝ≥0)

MISSING

Distinct21
Distinct (%)91.3%
Missing1524556
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean27.92078261
Minimum0.048
Maximum76
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:41.021728image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.048
5-th percentile1.122
Q17.675
median11.9
Q350.25
95-th percentile75.4
Maximum76
Range75.952
Interquartile range (IQR)42.575

Descriptive statistics

Standard deviation26.77502132
Coefficient of variation (CV)0.9589638549
Kurtosis-1.154690971
Mean27.92078261
Median Absolute Deviation (MAD)10.4
Skewness0.6728081437
Sum642.178
Variance716.9017668
MonotocityNot monotonic
2020-12-04T09:39:41.127374image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
53.72< 0.1%
 
762< 0.1%
 
15.71< 0.1%
 
8.451< 0.1%
 
8.71< 0.1%
 
641< 0.1%
 
1.081< 0.1%
 
701< 0.1%
 
0.0481< 0.1%
 
21.41< 0.1%
 
Other values (11)11< 0.1%
 
(Missing)1524556> 99.9%
 
ValueCountFrequency (%) 
0.0481< 0.1%
 
1.081< 0.1%
 
1.51< 0.1%
 
1.81< 0.1%
 
5.91< 0.1%
 
ValueCountFrequency (%) 
762< 0.1%
 
701< 0.1%
 
641< 0.1%
 
53.72< 0.1%
 
46.81< 0.1%
 

-elaidic-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

-gondoic-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

-mead-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

-erucic-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

-nervonic-acid_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

trans-fat_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct488
Distinct (%)0.2%
Missing1260475
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.04667960617
Minimum0
Maximum369
Zeros258345
Zeros (%)16.9%
Memory size11.6 MiB
2020-12-04T09:39:41.259809image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum369
Range369
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.06158146
Coefficient of variation (CV)22.74186838
Kurtosis57788.42962
Mean0.04667960617
Median Absolute Deviation (MAD)0
Skewness186.8116338
Sum12328.27071
Variance1.126955195
MonotocityNot monotonic
2020-12-04T09:39:41.383806image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
025834516.9%
 
0.1348< 0.1%
 
0.2287< 0.1%
 
3.57118< 0.1%
 
0.4115< 0.1%
 
1.79114< 0.1%
 
0.3104< 0.1%
 
1100< 0.1%
 
0.89100< 0.1%
 
0.8895< 0.1%
 
Other values (478)43780.3%
 
(Missing)126047582.7%
 
ValueCountFrequency (%) 
025834516.9%
 
0.00012< 0.1%
 
0.00031< 0.1%
 
0.00041< 0.1%
 
0.00052< 0.1%
 
ValueCountFrequency (%) 
3691< 0.1%
 
1302< 0.1%
 
1101< 0.1%
 
831< 0.1%
 
561< 0.1%
 

cholesterol_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct802
Distinct (%)0.3%
Missing1256522
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean0.0470848425
Minimum0
Maximum141
Zeros161260
Zeros (%)10.6%
Memory size11.6 MiB
2020-12-04T09:39:41.520672image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.022
95-th percentile0.089
Maximum141
Range141
Interquartile range (IQR)0.022

Descriptive statistics

Standard deviation1.361022687
Coefficient of variation (CV)28.90575002
Kurtosis3838.198683
Mean0.0470848425
Median Absolute Deviation (MAD)0
Skewness58.30991032
Sum12621.42163
Variance1.852382755
MonotocityNot monotonic
2020-12-04T09:39:41.647648image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016126010.6%
 
0.07144610.3%
 
0.10737700.2%
 
0.01237480.2%
 
0.08932070.2%
 
0.01831370.2%
 
0.05429330.2%
 
0.00428470.2%
 
0.00824970.2%
 
0.01724210.2%
 
Other values (792)777765.1%
 
(Missing)125652282.4%
 
ValueCountFrequency (%) 
016126010.6%
 
3.3e-081< 0.1%
 
4e-061< 0.1%
 
6.9e-061< 0.1%
 
1.4e-051< 0.1%
 
ValueCountFrequency (%) 
1411< 0.1%
 
1331< 0.1%
 
1271< 0.1%
 
116.9151< 0.1%
 
107.1431< 0.1%
 

carbohydrates_100g
Real number (ℝ≥0)

MISSING
ZEROS

Distinct14798
Distinct (%)1.2%
Missing314259
Missing (%)20.6%
Infinite0
Infinite (%)0.0%
Mean28.41369333
Minimum0
Maximum5310
Zeros96377
Zeros (%)6.3%
Memory size11.6 MiB
2020-12-04T09:39:41.791520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.57
median15.5
Q353.57
95-th percentile79
Maximum5310
Range5310
Interquartile range (IQR)50

Descriptive statistics

Standard deviation29.23542593
Coefficient of variation (CV)1.028920302
Kurtosis1077.478809
Mean28.41369333
Median Absolute Deviation (MAD)15
Skewness8.203811469
Sum34389661.31
Variance854.7101293
MonotocityNot monotonic
2020-12-04T09:39:41.925440image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0963776.3%
 
0.5290391.9%
 
1217981.4%
 
11108140.7%
 
12105190.7%
 
50103580.7%
 
1097950.6%
 
6093880.6%
 
286440.6%
 
1381460.5%
 
Other values (14788)99544265.3%
 
(Missing)31425920.6%
 
ValueCountFrequency (%) 
0963776.3%
 
1e-104< 0.1%
 
1e-092< 0.1%
 
1e-073< 0.1%
 
5e-071< 0.1%
 
ValueCountFrequency (%) 
53101< 0.1%
 
2916.671< 0.1%
 
24001< 0.1%
 
22001< 0.1%
 
21001< 0.1%
 

sugars_100g
Real number (ℝ)

MISSING
ZEROS

Distinct11330
Distinct (%)1.0%
Missing335417
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean13.7369552
Minimum-1
Maximum1350
Zeros169835
Zeros (%)11.1%
Memory size11.6 MiB
2020-12-04T09:39:42.062337image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10.7
median3.8
Q319.4
95-th percentile58.06
Maximum1350
Range1351
Interquartile range (IQR)18.7

Descriptive statistics

Standard deviation20.03485537
Coefficient of variation (CV)1.458464054
Kurtosis27.03310258
Mean13.7369552
Median Absolute Deviation (MAD)3.8
Skewness2.298015981
Sum16335465.12
Variance401.3954298
MonotocityNot monotonic
2020-12-04T09:39:42.202209image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016983511.1%
 
0.5578413.8%
 
1266301.7%
 
2141690.9%
 
0.1137290.9%
 
3.57124070.8%
 
0.6118590.8%
 
3117310.8%
 
0.7113700.7%
 
0.8102670.7%
 
Other values (11320)84932455.7%
 
(Missing)33541722.0%
 
ValueCountFrequency (%) 
-11< 0.1%
 
-0.11< 0.1%
 
016983511.1%
 
1e-102< 0.1%
 
1e-093< 0.1%
 
ValueCountFrequency (%) 
13501< 0.1%
 
9091< 0.1%
 
7141< 0.1%
 
5801< 0.1%
 
5521< 0.1%
 

-sucrose_100g
Real number (ℝ≥0)

MISSING

Distinct74
Distinct (%)57.8%
Missing1524451
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean13.94601562
Minimum0
Maximum99.8
Zeros10
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:42.345025image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5825
median8.25
Q316.7
95-th percentile43.5
Maximum99.8
Range99.8
Interquartile range (IQR)14.1175

Descriptive statistics

Standard deviation17.60708131
Coefficient of variation (CV)1.262516964
Kurtosis8.697688755
Mean13.94601562
Median Absolute Deviation (MAD)6.02
Skewness2.664675388
Sum1785.09
Variance310.0093123
MonotocityNot monotonic
2020-12-04T09:39:42.476003image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
010< 0.1%
 
2.238< 0.1%
 
5.25< 0.1%
 
0.15< 0.1%
 
43.55< 0.1%
 
265< 0.1%
 
74< 0.1%
 
7.54< 0.1%
 
233< 0.1%
 
93< 0.1%
 
Other values (64)76< 0.1%
 
(Missing)1524451> 99.9%
 
ValueCountFrequency (%) 
010< 0.1%
 
0.15< 0.1%
 
0.21< 0.1%
 
0.33< 0.1%
 
0.81< 0.1%
 
ValueCountFrequency (%) 
99.81< 0.1%
 
92.81< 0.1%
 
831< 0.1%
 
75.31< 0.1%
 
45.51< 0.1%
 

-glucose_100g
Real number (ℝ≥0)

MISSING

Distinct35
Distinct (%)64.8%
Missing1524525
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean8.903518519
Minimum0
Maximum55
Zeros3
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:42.595040image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.013
Q10.225
median2.04
Q315
95-th percentile30
Maximum55
Range55
Interquartile range (IQR)14.775

Descriptive statistics

Standard deviation12.60575253
Coefficient of variation (CV)1.415816961
Kurtosis2.464084916
Mean8.903518519
Median Absolute Deviation (MAD)2.03
Skewness1.659788546
Sum480.79
Variance158.9049968
MonotocityNot monotonic
2020-12-04T09:39:42.703633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%) 
0.28< 0.1%
 
305< 0.1%
 
03< 0.1%
 
53< 0.1%
 
152< 0.1%
 
1.42< 0.1%
 
0.52< 0.1%
 
22< 0.1%
 
171< 0.1%
 
231< 0.1%
 
Other values (25)25< 0.1%
 
(Missing)1524525> 99.9%
 
ValueCountFrequency (%) 
03< 0.1%
 
0.021< 0.1%
 
0.031< 0.1%
 
0.11< 0.1%
 
0.28< 0.1%
 
ValueCountFrequency (%) 
551< 0.1%
 
401< 0.1%
 
305< 0.1%
 
23.21< 0.1%
 
23.11< 0.1%
 

-fructose_100g
Real number (ℝ≥0)

MISSING

Distinct48
Distinct (%)64.0%
Missing1524504
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean25.458
Minimum0
Maximum100
Zeros6
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:42.834610image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.7
median19.6
Q345
95-th percentile65.43
Maximum100
Range100
Interquartile range (IQR)44.3

Descriptive statistics

Standard deviation26.2939581
Coefficient of variation (CV)1.032836755
Kurtosis-0.2144058105
Mean25.458
Median Absolute Deviation (MAD)19.5
Skewness0.7376240338
Sum1909.35
Variance691.3722324
MonotocityNot monotonic
2020-12-04T09:39:42.963569image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%) 
06< 0.1%
 
405< 0.1%
 
0.24< 0.1%
 
0.13< 0.1%
 
55.13< 0.1%
 
533< 0.1%
 
252< 0.1%
 
0.92< 0.1%
 
1002< 0.1%
 
56.12< 0.1%
 
Other values (38)43< 0.1%
 
(Missing)1524504> 99.9%
 
ValueCountFrequency (%) 
06< 0.1%
 
0.021< 0.1%
 
0.031< 0.1%
 
0.13< 0.1%
 
0.111< 0.1%
 
ValueCountFrequency (%) 
1002< 0.1%
 
701< 0.1%
 
691< 0.1%
 
63.92< 0.1%
 
601< 0.1%
 

-lactose_100g
Real number (ℝ≥0)

MISSING

Distinct107
Distinct (%)15.3%
Missing1523879
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3.361411129
Minimum0
Maximum74.5
Zeros277
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:43.093021image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.01
Q31
95-th percentile25.265
Maximum74.5
Range74.5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation10.78525519
Coefficient of variation (CV)3.208549856
Kurtosis15.75627481
Mean3.361411129
Median Absolute Deviation (MAD)0.01
Skewness4.036508472
Sum2352.98779
Variance116.3217296
MonotocityNot monotonic
2020-12-04T09:39:43.221985image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0277< 0.1%
 
0.01104< 0.1%
 
0.195< 0.1%
 
135< 0.1%
 
2.9821< 0.1%
 
0.513< 0.1%
 
0.29< 0.1%
 
4.87< 0.1%
 
4.34< 0.1%
 
5.24< 0.1%
 
Other values (97)131< 0.1%
 
(Missing)1523879> 99.9%
 
ValueCountFrequency (%) 
0277< 0.1%
 
0.00011< 0.1%
 
0.003491< 0.1%
 
0.00421< 0.1%
 
0.0051< 0.1%
 
ValueCountFrequency (%) 
74.51< 0.1%
 
58.51< 0.1%
 
57.42< 0.1%
 
57.31< 0.1%
 
56.52< 0.1%
 

-maltose_100g
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)100.0%
Missing1524570
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean11.82222222
Minimum0
Maximum39.2
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:43.351434image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04
Q10.5
median3
Q322
95-th percentile37.92
Maximum39.2
Range39.2
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation16.16978492
Coefficient of variation (CV)1.367744965
Kurtosis-0.6831703304
Mean11.82222222
Median Absolute Deviation (MAD)2.9
Skewness1.088034417
Sum106.4
Variance261.4619444
MonotocityNot monotonic
2020-12-04T09:39:43.451137image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
221< 0.1%
 
39.21< 0.1%
 
0.51< 0.1%
 
0.11< 0.1%
 
31< 0.1%
 
4.81< 0.1%
 
0.81< 0.1%
 
361< 0.1%
 
01< 0.1%
 
(Missing)1524570> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.11< 0.1%
 
0.51< 0.1%
 
0.81< 0.1%
 
31< 0.1%
 
ValueCountFrequency (%) 
39.21< 0.1%
 
361< 0.1%
 
221< 0.1%
 
4.81< 0.1%
 
31< 0.1%
 

-maltodextrins_100g
Real number (ℝ≥0)

MISSING

Distinct15
Distinct (%)88.2%
Missing1524562
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean11.19458824
Minimum0.008
Maximum34.4
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:43.560258image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.008
5-th percentile1.2016
Q11.8
median10.3
Q316.1
95-th percentile28.88
Maximum34.4
Range34.392
Interquartile range (IQR)14.3

Descriptive statistics

Standard deviation10.07785433
Coefficient of variation (CV)0.9002434138
Kurtosis0.137267862
Mean11.19458824
Median Absolute Deviation (MAD)8.1
Skewness0.8207054225
Sum190.308
Variance101.5631479
MonotocityNot monotonic
2020-12-04T09:39:43.657970image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
1.53< 0.1%
 
0.0081< 0.1%
 
27.51< 0.1%
 
201< 0.1%
 
151< 0.1%
 
2.21< 0.1%
 
13.51< 0.1%
 
1.81< 0.1%
 
17.81< 0.1%
 
91< 0.1%
 
Other values (5)5< 0.1%
 
(Missing)1524562> 99.9%
 
ValueCountFrequency (%) 
0.0081< 0.1%
 
1.53< 0.1%
 
1.81< 0.1%
 
2.21< 0.1%
 
3.41< 0.1%
 
ValueCountFrequency (%) 
34.41< 0.1%
 
27.51< 0.1%
 
201< 0.1%
 
17.81< 0.1%
 
16.11< 0.1%
 

starch_100g
Real number (ℝ≥0)

MISSING

Distinct222
Distinct (%)49.2%
Missing1524128
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean28.25977095
Minimum0
Maximum87.8
Zeros33
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:44.256643image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.85
median28
Q346.4
95-th percentile70.7
Maximum87.8
Range87.8
Interquartile range (IQR)43.55

Descriptive statistics

Standard deviation24.6903608
Coefficient of variation (CV)0.8736928845
Kurtosis-1.181688255
Mean28.25977095
Median Absolute Deviation (MAD)23.7
Skewness0.387265557
Sum12745.1567
Variance609.6139164
MonotocityNot monotonic
2020-12-04T09:39:44.379650image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
033< 0.1%
 
0.517< 0.1%
 
3912< 0.1%
 
3812< 0.1%
 
7111< 0.1%
 
438< 0.1%
 
507< 0.1%
 
16< 0.1%
 
416< 0.1%
 
16.76< 0.1%
 
Other values (212)333< 0.1%
 
(Missing)1524128> 99.9%
 
ValueCountFrequency (%) 
033< 0.1%
 
0.011< 0.1%
 
0.01671< 0.1%
 
0.041< 0.1%
 
0.082< 0.1%
 
ValueCountFrequency (%) 
87.81< 0.1%
 
87.51< 0.1%
 
781< 0.1%
 
771< 0.1%
 
761< 0.1%
 

polyols_100g
Real number (ℝ≥0)

MISSING

Distinct344
Distinct (%)9.9%
Missing1521095
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean30.88254851
Minimum0
Maximum100
Zeros583
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:44.517049image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median15
Q361.3
95-th percentile97.5
Maximum100
Range100
Interquartile range (IQR)57.3

Descriptive statistics

Standard deviation33.44415565
Coefficient of variation (CV)1.082946753
Kurtosis-0.74305473
Mean30.88254851
Median Absolute Deviation (MAD)15
Skewness0.8682667475
Sum107594.799
Variance1118.511547
MonotocityNot monotonic
2020-12-04T09:39:44.656913image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0583< 0.1%
 
100132< 0.1%
 
7114< 0.1%
 
8107< 0.1%
 
6106< 0.1%
 
5105< 0.1%
 
7497< 0.1%
 
494< 0.1%
 
978< 0.1%
 
1877< 0.1%
 
Other values (334)19910.1%
 
(Missing)152109599.8%
 
ValueCountFrequency (%) 
0583< 0.1%
 
0.0011< 0.1%
 
0.031< 0.1%
 
0.0381< 0.1%
 
0.075< 0.1%
 
ValueCountFrequency (%) 
100132< 0.1%
 
99.62< 0.1%
 
99.52< 0.1%
 
99.31< 0.1%
 
997< 0.1%
 

fiber_100g
Real number (ℝ)

MISSING
SKEWED
ZEROS

Distinct1979
Distinct (%)0.4%
Missing1071773
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean2.961798549
Minimum-20
Maximum900
Zeros141660
Zeros (%)9.3%
Memory size11.6 MiB
2020-12-04T09:39:44.793810image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-20
5-th percentile0
Q10
median1.6
Q33.6
95-th percentile10.7
Maximum900
Range920
Interquartile range (IQR)3.6

Descriptive statistics

Standard deviation5.496283775
Coefficient of variation (CV)1.855725055
Kurtosis2896.699442
Mean2.961798549
Median Absolute Deviation (MAD)1.6
Skewness26.53871442
Sum1341120.154
Variance30.20913534
MonotocityNot monotonic
2020-12-04T09:39:44.921288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
01416609.3%
 
3.6155661.0%
 
0.599740.7%
 
0.886850.6%
 
284980.6%
 
1.882540.5%
 
181230.5%
 
3.379570.5%
 
1.276740.5%
 
2.474830.5%
 
Other values (1969)22893215.0%
 
(Missing)107177370.3%
 
ValueCountFrequency (%) 
-201< 0.1%
 
-6.71< 0.1%
 
-6.672< 0.1%
 
-12< 0.1%
 
-0.4173< 0.1%
 
ValueCountFrequency (%) 
9001< 0.1%
 
7001< 0.1%
 
6251< 0.1%
 
5001< 0.1%
 
4391< 0.1%
 

-soluble-fiber_100g
Real number (ℝ≥0)

MISSING

Distinct41
Distinct (%)1.1%
Missing1520979
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean2.415419444
Minimum0
Maximum61
Zeros996
Zeros (%)0.1%
Memory size11.6 MiB
2020-12-04T09:39:45.045284image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile6
Maximum61
Range61
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.658103413
Coefficient of variation (CV)1.514479575
Kurtosis77.10293964
Mean2.415419444
Median Absolute Deviation (MAD)2
Skewness6.858075733
Sum8695.51
Variance13.38172058
MonotocityNot monotonic
2020-12-04T09:39:45.192101image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%) 
09960.1%
 
27780.1%
 
1594< 0.1%
 
3384< 0.1%
 
4323< 0.1%
 
5296< 0.1%
 
849< 0.1%
 
645< 0.1%
 
725< 0.1%
 
1824< 0.1%
 
Other values (31)86< 0.1%
 
(Missing)152097999.8%
 
ValueCountFrequency (%) 
09960.1%
 
1594< 0.1%
 
1.491< 0.1%
 
1.821< 0.1%
 
27780.1%
 
ValueCountFrequency (%) 
611< 0.1%
 
601< 0.1%
 
521< 0.1%
 
501< 0.1%
 
481< 0.1%
 

-insoluble-fiber_100g
Real number (ℝ≥0)

MISSING

Distinct57
Distinct (%)1.7%
Missing1521249
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean4.261309309
Minimum0
Maximum46
Zeros726
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:45.393443image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile11
Maximum46
Range46
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.894566997
Coefficient of variation (CV)1.148606365
Kurtosis13.9222893
Mean4.261309309
Median Absolute Deviation (MAD)2
Skewness2.836024928
Sum14190.16
Variance23.95678609
MonotocityNot monotonic
2020-12-04T09:39:45.578947image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0726< 0.1%
 
2451< 0.1%
 
5429< 0.1%
 
1392< 0.1%
 
4233< 0.1%
 
9181< 0.1%
 
3175< 0.1%
 
7149< 0.1%
 
8136< 0.1%
 
6132< 0.1%
 
Other values (47)326< 0.1%
 
(Missing)152124999.8%
 
ValueCountFrequency (%) 
0726< 0.1%
 
1392< 0.1%
 
2451< 0.1%
 
2.081< 0.1%
 
2.561< 0.1%
 
ValueCountFrequency (%) 
461< 0.1%
 
45.81< 0.1%
 
431< 0.1%
 
393< 0.1%
 
381< 0.1%
 

proteins_100g
Real number (ℝ)

MISSING
SKEWED
ZEROS

Distinct9099
Distinct (%)0.8%
Missing312602
Missing (%)20.5%
Infinite0
Infinite (%)0.0%
Mean8.503551606
Minimum-500
Maximum2500
Zeros161390
Zeros (%)10.6%
Memory size11.6 MiB
2020-12-04T09:39:45.729236image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-500
5-th percentile0
Q11.2
median5.88
Q312
95-th percentile25.3
Maximum2500
Range3000
Interquartile range (IQR)10.8

Descriptive statistics

Standard deviation10.86146103
Coefficient of variation (CV)1.277285249
Kurtosis6507.709791
Mean8.503551606
Median Absolute Deviation (MAD)5.08
Skewness35.42074198
Sum10306108.97
Variance117.9713357
MonotocityNot monotonic
2020-12-04T09:39:45.864675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016139010.6%
 
0.5273371.8%
 
10165621.1%
 
12165011.1%
 
20144500.9%
 
1143730.9%
 
11134590.9%
 
25133340.9%
 
13124860.8%
 
5123920.8%
 
Other values (9089)90969359.7%
 
(Missing)31260220.5%
 
ValueCountFrequency (%) 
-5001< 0.1%
 
016139010.6%
 
1e-102< 0.1%
 
1e-073< 0.1%
 
1e-064< 0.1%
 
ValueCountFrequency (%) 
25001< 0.1%
 
24001< 0.1%
 
20001< 0.1%
 
18001< 0.1%
 
15001< 0.1%
 

casein_100g
Real number (ℝ≥0)

MISSING

Distinct26
Distinct (%)63.4%
Missing1524538
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean4.382195122
Minimum0.7
Maximum10.7
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:46.000084image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.7
5-th percentile0.92
Q11.4
median3.9
Q37
95-th percentile10
Maximum10.7
Range10
Interquartile range (IQR)5.6

Descriptive statistics

Standard deviation3.031830728
Coefficient of variation (CV)0.6918520612
Kurtosis-0.8685592246
Mean4.382195122
Median Absolute Deviation (MAD)2.5
Skewness0.5928879214
Sum179.67
Variance9.191997561
MonotocityNot monotonic
2020-12-04T09:39:46.108211image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%) 
1.46< 0.1%
 
2.96< 0.1%
 
4.73< 0.1%
 
1.12< 0.1%
 
7.42< 0.1%
 
8.62< 0.1%
 
10.71< 0.1%
 
4.21< 0.1%
 
4.81< 0.1%
 
4.951< 0.1%
 
Other values (16)16< 0.1%
 
(Missing)1524538> 99.9%
 
ValueCountFrequency (%) 
0.71< 0.1%
 
0.91< 0.1%
 
0.921< 0.1%
 
1.12< 0.1%
 
1.31< 0.1%
 
ValueCountFrequency (%) 
10.71< 0.1%
 
10.21< 0.1%
 
101< 0.1%
 
9.31< 0.1%
 
8.62< 0.1%
 

serum-proteins_100g
Real number (ℝ≥0)

MISSING

Distinct24
Distinct (%)64.9%
Missing1524542
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean4.067297297
Minimum0
Maximum21
Zeros2
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:46.218324image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.08
Q10.4
median3
Q35.4
95-th percentile12.4
Maximum21
Range21
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.825766288
Coefficient of variation (CV)1.18647985
Kurtosis5.907229247
Mean4.067297297
Median Absolute Deviation (MAD)2.6
Skewness2.234027843
Sum150.49
Variance23.28802027
MonotocityNot monotonic
2020-12-04T09:39:46.322983image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%) 
0.36< 0.1%
 
5.83< 0.1%
 
4.73< 0.1%
 
02< 0.1%
 
0.42< 0.1%
 
32< 0.1%
 
1.92< 0.1%
 
0.51< 0.1%
 
5.21< 0.1%
 
0.71< 0.1%
 
Other values (14)14< 0.1%
 
(Missing)1524542> 99.9%
 
ValueCountFrequency (%) 
02< 0.1%
 
0.11< 0.1%
 
0.36< 0.1%
 
0.42< 0.1%
 
0.51< 0.1%
 
ValueCountFrequency (%) 
211< 0.1%
 
201< 0.1%
 
10.51< 0.1%
 
81< 0.1%
 
7.171< 0.1%
 

nucleotides_100g
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)71.4%
Missing1524565
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.2186857143
Minimum0.0025
Maximum2.8
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:46.422675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.0025
5-th percentile0.01095
Q10.0204
median0.022
Q30.02375
95-th percentile0.99625
Maximum2.8
Range2.7975
Interquartile range (IQR)0.00335

Descriptive statistics

Standard deviation0.7429748353
Coefficient of variation (CV)3.397454826
Kurtosis13.99797839
Mean0.2186857143
Median Absolute Deviation (MAD)0.002
Skewness3.741277691
Sum3.0616
Variance0.5520116059
MonotocityNot monotonic
2020-12-04T09:39:46.511956image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.0224< 0.1%
 
0.0242< 0.1%
 
0.00251< 0.1%
 
0.0181< 0.1%
 
0.0251< 0.1%
 
0.01551< 0.1%
 
2.81< 0.1%
 
0.0231< 0.1%
 
0.02161< 0.1%
 
0.021< 0.1%
 
(Missing)1524565> 99.9%
 
ValueCountFrequency (%) 
0.00251< 0.1%
 
0.01551< 0.1%
 
0.0181< 0.1%
 
0.021< 0.1%
 
0.02161< 0.1%
 
ValueCountFrequency (%) 
2.81< 0.1%
 
0.0251< 0.1%
 
0.0242< 0.1%
 
0.0231< 0.1%
 
0.0224< 0.1%
 

salt_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct16476
Distinct (%)1.4%
Missing338988
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean1.777119327
Minimum0
Maximum66700
Zeros169618
Zeros (%)11.1%
Memory size11.6 MiB
2020-12-04T09:39:46.682053image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.06
median0.54102
Q31.37
95-th percentile3.9
Maximum66700
Range66700
Interquartile range (IQR)1.31

Descriptive statistics

Standard deviation74.4517598
Coefficient of variation (CV)41.89463176
Kurtosis610835.0899
Mean1.777119327
Median Absolute Deviation (MAD)0.53102
Skewness735.3130733
Sum2106936.68
Variance5543.064537
MonotocityNot monotonic
2020-12-04T09:39:46.823413image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016961811.1%
 
0.1391212.6%
 
0.01319842.1%
 
1284811.9%
 
1.5199921.3%
 
1.2159581.0%
 
2159521.0%
 
0.03159481.0%
 
1.1159061.0%
 
0.02155651.0%
 
Other values (16466)81706653.6%
 
(Missing)33898822.2%
 
ValueCountFrequency (%) 
016961811.1%
 
1e-101< 0.1%
 
8e-101< 0.1%
 
1e-091< 0.1%
 
7.2e-091< 0.1%
 
ValueCountFrequency (%) 
667001< 0.1%
 
396001< 0.1%
 
46701< 0.1%
 
42701< 0.1%
 
32101< 0.1%
 

sodium_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct16555
Distinct (%)1.4%
Missing338993
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean0.7108912916
Minimum0
Maximum26700
Zeros169613
Zeros (%)11.1%
Memory size11.6 MiB
2020-12-04T09:39:46.988615image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.024
median0.216408
Q30.548
95-th percentile1.56
Maximum26700
Range26700
Interquartile range (IQR)0.524

Descriptive statistics

Standard deviation29.77843097
Coefficient of variation (CV)41.88886729
Kurtosis611976.3223
Mean0.7108912916
Median Absolute Deviation (MAD)0.212408
Skewness735.8927624
Sum842822.7628
Variance886.7549511
MonotocityNot monotonic
2020-12-04T09:39:47.140391image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016961311.1%
 
0.04391302.6%
 
0.004319882.1%
 
0.4284811.9%
 
0.6199821.3%
 
0.012162021.1%
 
0.48159421.0%
 
0.8159371.0%
 
0.44158871.0%
 
0.008155621.0%
 
Other values (16545)81686253.6%
 
(Missing)33899322.2%
 
ValueCountFrequency (%) 
016961311.1%
 
3e-101< 0.1%
 
4e-101< 0.1%
 
2.9e-091< 0.1%
 
4e-092< 0.1%
 
ValueCountFrequency (%) 
267001< 0.1%
 
158001< 0.1%
 
18701< 0.1%
 
17101< 0.1%
 
12901< 0.1%
 

alcohol_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct236
Distinct (%)1.4%
Missing1507229
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean5763693.252
Minimum0
Maximum1e+11
Zeros10799
Zeros (%)0.7%
Memory size11.6 MiB
2020-12-04T09:39:47.286213image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.5
95-th percentile16.275
Maximum1e+11
Range1e+11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation759189618
Coefficient of variation (CV)131.7192961
Kurtosis17350
Mean5763693.252
Median Absolute Deviation (MAD)0
Skewness131.7193987
Sum1.000000779e+11
Variance5.76368876e+17
MonotocityNot monotonic
2020-12-04T09:39:47.436501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0107990.7%
 
12.5437< 0.1%
 
5432< 0.1%
 
13380< 0.1%
 
12336< 0.1%
 
40293< 0.1%
 
13.5243< 0.1%
 
4.5214< 0.1%
 
6206< 0.1%
 
5.5177< 0.1%
 
Other values (226)38330.3%
 
(Missing)150722998.9%
 
ValueCountFrequency (%) 
0107990.7%
 
0.00021< 0.1%
 
0.021< 0.1%
 
0.033< 0.1%
 
0.054< 0.1%
 
ValueCountFrequency (%) 
1e+111< 0.1%
 
10019< 0.1%
 
992< 0.1%
 
911< 0.1%
 
901< 0.1%
 

vitamin-a_100g
Real number (ℝ)

MISSING
SKEWED
ZEROS

Distinct3085
Distinct (%)1.5%
Missing1312667
Missing (%)86.1%
Infinite0
Infinite (%)0.0%
Mean0.03962911289
Minimum-0.0003396
Maximum2200
Zeros118140
Zeros (%)7.7%
Memory size11.6 MiB
2020-12-04T09:39:47.584806image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.0003396
5-th percentile0
Q10
median0
Q30.0001071
95-th percentile0.0006081
Maximum2200
Range2200.00034
Interquartile range (IQR)0.0001071

Descriptive statistics

Standard deviation6.286976968
Coefficient of variation (CV)158.6454127
Kurtosis76542.54637
Mean0.03962911289
Median Absolute Deviation (MAD)0
Skewness249.7897214
Sum8397.884571
Variance39.52607939
MonotocityNot monotonic
2020-12-04T09:39:47.713763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
01181407.7%
 
0.000321335150.2%
 
0.000214232990.2%
 
0.000107126210.2%
 
9.99e-0525140.2%
 
6.24e-0520550.1%
 
0.000200117040.1%
 
7.5e-0510780.1%
 
0.000428710070.1%
 
5.31e-059820.1%
 
Other values (3075)749974.9%
 
(Missing)131266786.1%
 
ValueCountFrequency (%) 
-0.00033961< 0.1%
 
01181407.7%
 
1e-081< 0.1%
 
1.6e-081< 0.1%
 
3e-081< 0.1%
 
ValueCountFrequency (%) 
22001< 0.1%
 
9001< 0.1%
 
8002< 0.1%
 
7331< 0.1%
 
5211< 0.1%
 

beta-carotene_100g
Real number (ℝ≥0)

MISSING

Distinct52
Distinct (%)64.2%
Missing1524498
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.5460588889
Minimum0
Maximum38
Zeros6
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:47.853110image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.2e-05
median0.0007
Q30.067
95-th percentile0.4
Maximum38
Range38
Interquartile range (IQR)0.066968

Descriptive statistics

Standard deviation4.217767876
Coefficient of variation (CV)7.724016516
Kurtosis80.66557351
Mean0.5460588889
Median Absolute Deviation (MAD)0.000693
Skewness8.972802671
Sum44.23077
Variance17.78956586
MonotocityNot monotonic
2020-12-04T09:39:47.994469image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
06< 0.1%
 
1.2e-056< 0.1%
 
3.2e-056< 0.1%
 
0.00034< 0.1%
 
0.143< 0.1%
 
9e-062< 0.1%
 
7e-062< 0.1%
 
0.00162< 0.1%
 
2.5e-052< 0.1%
 
0.22< 0.1%
 
Other values (42)46< 0.1%
 
(Missing)1524498> 99.9%
 
ValueCountFrequency (%) 
06< 0.1%
 
7e-062< 0.1%
 
9e-062< 0.1%
 
1.2e-056< 0.1%
 
2.5e-052< 0.1%
 
ValueCountFrequency (%) 
381< 0.1%
 
1.11< 0.1%
 
11< 0.1%
 
0.4331< 0.1%
 
0.41< 0.1%
 

vitamin-d_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct579
Distinct (%)6.3%
Missing1515370
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean0.03789363215
Minimum0
Maximum100
Zeros544
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:48.141815image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11e-06
median1.2e-06
Q33.45e-06
95-th percentile1.19e-05
Maximum100
Range100
Interquartile range (IQR)2.45e-06

Descriptive statistics

Standard deviation1.511770427
Coefficient of variation (CV)39.89510483
Kurtosis4154.33349
Mean0.03789363215
Median Absolute Deviation (MAD)6.5e-07
Skewness63.13562479
Sum348.9624585
Variance2.285449824
MonotocityNot monotonic
2020-12-04T09:39:48.273256image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.05e-0616180.1%
 
0544< 0.1%
 
7.5e-07533< 0.1%
 
1e-06333< 0.1%
 
3.325e-06317< 0.1%
 
1.25e-06298< 0.1%
 
7.5e-06248< 0.1%
 
4.25e-07235< 0.1%
 
1.175e-06195< 0.1%
 
2e-06147< 0.1%
 
Other values (569)47410.3%
 
(Missing)151537099.4%
 
ValueCountFrequency (%) 
0544< 0.1%
 
7e-102< 0.1%
 
3e-091< 0.1%
 
3.1e-091< 0.1%
 
3.7e-091< 0.1%
 
ValueCountFrequency (%) 
1002< 0.1%
 
161< 0.1%
 
12.51< 0.1%
 
101< 0.1%
 
8.42< 0.1%
 

vitamin-e_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct509
Distinct (%)16.5%
Missing1521501
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean0.3488957124
Minimum0
Maximum125
Zeros22
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:48.409164image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0007
Q10.0018
median0.0055
Q30.014
95-th percentile0.05015
Maximum125
Range125
Interquartile range (IQR)0.0122

Descriptive statistics

Standard deviation3.93647087
Coefficient of variation (CV)11.28265762
Kurtosis555.9048409
Mean0.3488957124
Median Absolute Deviation (MAD)0.0042
Skewness21.20208075
Sum1073.901003
Variance15.49580291
MonotocityNot monotonic
2020-12-04T09:39:48.555447image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0018325< 0.1%
 
0.012137< 0.1%
 
0.00289< 0.1%
 
0.0288< 0.1%
 
0.0179< 0.1%
 
0.01165< 0.1%
 
0.00358< 0.1%
 
0.003657< 0.1%
 
0.00557< 0.1%
 
0.00653< 0.1%
 
Other values (499)20700.1%
 
(Missing)152150199.8%
 
ValueCountFrequency (%) 
022< 0.1%
 
3.2e-091< 0.1%
 
5.2e-091< 0.1%
 
1e-071< 0.1%
 
5e-071< 0.1%
 
ValueCountFrequency (%) 
1251< 0.1%
 
99.51< 0.1%
 
901< 0.1%
 
36.91< 0.1%
 
33.91< 0.1%
 

vitamin-k_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct375
Distinct (%)34.8%
Missing1523502
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean0.03296503188
Minimum0
Maximum31.25
Zeros51
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:48.695848image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7e-07
Q16.2e-06
median2.5e-05
Q38.47e-05
95-th percentile0.00081056
Maximum31.25
Range31.25
Interquartile range (IQR)7.85e-05

Descriptive statistics

Standard deviation0.9591371271
Coefficient of variation (CV)29.09559228
Kurtosis1045.918759
Mean0.03296503188
Median Absolute Deviation (MAD)2e-05
Skewness32.15805483
Sum35.50333934
Variance0.9199440285
MonotocityNot monotonic
2020-12-04T09:39:48.820836image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
051< 0.1%
 
2.94e-0523< 0.1%
 
2.86e-0523< 0.1%
 
2e-0522< 0.1%
 
5.7e-0622< 0.1%
 
2.4e-0520< 0.1%
 
5.71e-0520< 0.1%
 
5e-0620< 0.1%
 
4e-0619< 0.1%
 
2.5e-0515< 0.1%
 
Other values (365)8420.1%
 
(Missing)152350299.9%
 
ValueCountFrequency (%) 
051< 0.1%
 
2e-071< 0.1%
 
7e-074< 0.1%
 
9e-072< 0.1%
 
1.2e-063< 0.1%
 
ValueCountFrequency (%) 
31.251< 0.1%
 
3.81< 0.1%
 
0.14291< 0.1%
 
0.06961< 0.1%
 
0.03341< 0.1%
 

vitamin-c_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct1568
Distinct (%)0.7%
Missing1305092
Missing (%)85.6%
Infinite0
Infinite (%)0.0%
Mean0.02574893259
Minimum0
Maximum100
Zeros136210
Zeros (%)8.9%
Memory size11.6 MiB
2020-12-04T09:39:48.960189image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.004
95-th percentile0.0357
Maximum100
Range100
Interquartile range (IQR)0.004

Descriptive statistics

Standard deviation0.7843743692
Coefficient of variation (CV)30.46240331
Kurtosis6894.004307
Mean0.02574893259
Median Absolute Deviation (MAD)0
Skewness74.79587134
Sum5651.555967
Variance0.6152431511
MonotocityNot monotonic
2020-12-04T09:39:49.094136image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
01362108.9%
 
0.00122030.1%
 
0.00418230.1%
 
0.004317880.1%
 
0.002117500.1%
 
0.02517400.1%
 
0.0317350.1%
 
0.021414580.1%
 
0.00813910.1%
 
0.001113300.1%
 
Other values (1558)680594.5%
 
(Missing)130509285.6%
 
ValueCountFrequency (%) 
01362108.9%
 
3e-091< 0.1%
 
1.8e-071< 0.1%
 
2e-072< 0.1%
 
2.53e-071< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
901< 0.1%
 
871< 0.1%
 
85.721< 0.1%
 
841< 0.1%
 

vitamin-b1_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct772
Distinct (%)3.3%
Missing1501394
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean0.6911407502
Minimum0
Maximum910
Zeros9948
Zeros (%)0.7%
Memory size11.6 MiB
2020-12-04T09:39:49.229511image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.00077
Q30.001
95-th percentile0.0408
Maximum910
Range910
Interquartile range (IQR)0.001

Descriptive statistics

Standard deviation11.01879712
Coefficient of variation (CV)15.94291338
Kurtosis2753.001133
Mean0.6911407502
Median Absolute Deviation (MAD)0.00077
Skewness42.62376456
Sum16024.09829
Variance121.4138899
MonotocityNot monotonic
2020-12-04T09:39:49.359999image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
099480.7%
 
0.00178600.5%
 
0.0028690.1%
 
0.003153< 0.1%
 
0.0009146< 0.1%
 
0.0011125< 0.1%
 
0.005118< 0.1%
 
0.004104< 0.1%
 
0.0001796< 0.1%
 
0.0003396< 0.1%
 
Other values (762)36700.2%
 
(Missing)150139498.5%
 
ValueCountFrequency (%) 
099480.7%
 
3e-102< 0.1%
 
4e-101< 0.1%
 
8e-101< 0.1%
 
9e-101< 0.1%
 
ValueCountFrequency (%) 
9101< 0.1%
 
6671< 0.1%
 
3031< 0.1%
 
3001< 0.1%
 
2671< 0.1%
 

vitamin-b2_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct1416
Distinct (%)6.4%
Missing1502296
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean0.02703979119
Minimum0
Maximum41
Zeros615
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:49.495862image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.8e-05
Q10.00021
median0.000357
Q30.00083
95-th percentile0.014167
Maximum41
Range41
Interquartile range (IQR)0.00062

Descriptive statistics

Standard deviation0.4199343358
Coefficient of variation (CV)15.5302359
Kurtosis6400.302439
Mean0.02703979119
Median Absolute Deviation (MAD)0.000207
Skewness71.83045853
Sum602.5276672
Variance0.1763448464
MonotocityNot monotonic
2020-12-04T09:39:49.628823image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00045511140.1%
 
0615< 0.1%
 
0.00034528< 0.1%
 
0.000304528< 0.1%
 
0.000243341< 0.1%
 
0.001417300< 0.1%
 
0.000327281< 0.1%
 
0.000121266< 0.1%
 
0.00021256< 0.1%
 
0.000357254< 0.1%
 
Other values (1406)178001.2%
 
(Missing)150229698.5%
 
ValueCountFrequency (%) 
0615< 0.1%
 
3e-101< 0.1%
 
5e-101< 0.1%
 
2.3e-091< 0.1%
 
2.5e-091< 0.1%
 
ValueCountFrequency (%) 
411< 0.1%
 
35.4166671< 0.1%
 
121< 0.1%
 
11.91< 0.1%
 
6.81< 0.1%
 

vitamin-pp_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct1640
Distinct (%)7.0%
Missing1501184
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean0.03254777216
Minimum0
Maximum69
Zeros445
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:49.760257image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0005
Q10.002941
median0.005
Q30.0086
95-th percentile0.019444
Maximum69
Range69
Interquartile range (IQR)0.005659

Descriptive statistics

Standard deviation0.7565612633
Coefficient of variation (CV)23.24464052
Kurtosis4826.867087
Mean0.03254777216
Median Absolute Deviation (MAD)0.0023
Skewness61.83353601
Sum761.4551296
Variance0.5723849452
MonotocityNot monotonic
2020-12-04T09:39:49.887238image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00714313160.1%
 
0.0053578330.1%
 
0.004527< 0.1%
 
0.002857474< 0.1%
 
0445< 0.1%
 
0.004286400< 0.1%
 
0.005714394< 0.1%
 
0.000833338< 0.1%
 
0.003846323< 0.1%
 
0.016667321< 0.1%
 
Other values (1630)180241.2%
 
(Missing)150118498.5%
 
ValueCountFrequency (%) 
0445< 0.1%
 
3.1e-091< 0.1%
 
8.8e-091< 0.1%
 
1.34e-081< 0.1%
 
1.5e-081< 0.1%
 
ValueCountFrequency (%) 
691< 0.1%
 
591< 0.1%
 
361< 0.1%
 
162< 0.1%
 
15.91< 0.1%
 

vitamin-b6_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct1123
Distinct (%)7.2%
Missing1508950
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean0.245293699
Minimum0
Maximum467
Zeros348
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:50.027112image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3e-05
Q10.000208
median0.000571
Q30.001316
95-th percentile0.006667
Maximum467
Range467
Interquartile range (IQR)0.001108

Descriptive statistics

Standard deviation6.904626027
Coefficient of variation (CV)28.14840355
Kurtosis2759.478406
Mean0.245293699
Median Absolute Deviation (MAD)0.000436
Skewness47.78936151
Sum3833.695221
Variance47.67386058
MonotocityNot monotonic
2020-12-04T09:39:50.763144image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0348< 0.1%
 
0.001667348< 0.1%
 
8.3e-05328< 0.1%
 
0.0004324< 0.1%
 
5e-05313< 0.1%
 
0.000571302< 0.1%
 
0.000385267< 0.1%
 
0.000714247< 0.1%
 
0.00021239< 0.1%
 
0.000833235< 0.1%
 
Other values (1113)126780.8%
 
(Missing)150895099.0%
 
ValueCountFrequency (%) 
0348< 0.1%
 
3e-101< 0.1%
 
9e-102< 0.1%
 
1.2e-091< 0.1%
 
7e-081< 0.1%
 
ValueCountFrequency (%) 
4671< 0.1%
 
4501< 0.1%
 
2202< 0.1%
 
1882< 0.1%
 
1801< 0.1%
 

vitamin-b9_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct710
Distinct (%)7.2%
Missing1514685
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean0.2330820664
Minimum0
Maximum334
Zeros214
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:50.905496image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3e-05
Q13.5e-05
median6.5e-05
Q30.000141
95-th percentile0.000334
Maximum334
Range334
Interquartile range (IQR)0.000106

Descriptive statistics

Standard deviation6.471252927
Coefficient of variation (CV)27.76383883
Kurtosis1268.005393
Mean0.2330820664
Median Absolute Deviation (MAD)3.5e-05
Skewness33.62196279
Sum2306.113965
Variance41.87711445
MonotocityNot monotonic
2020-12-04T09:39:51.039912image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3e-05579< 0.1%
 
5.6e-05516< 0.1%
 
2.8e-05274< 0.1%
 
0214< 0.1%
 
0.000196196< 0.1%
 
6e-05172< 0.1%
 
0.0002171< 0.1%
 
0.000166159< 0.1%
 
5.7e-05147< 0.1%
 
5.5e-05132< 0.1%
 
Other values (700)73340.5%
 
(Missing)151468599.4%
 
ValueCountFrequency (%) 
0214< 0.1%
 
1e-101< 0.1%
 
2e-101< 0.1%
 
3e-101< 0.1%
 
2.4e-091< 0.1%
 
ValueCountFrequency (%) 
3341< 0.1%
 
2003< 0.1%
 
1951< 0.1%
 
1701< 0.1%
 
1663< 0.1%
 

folates_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct418
Distinct (%)5.0%
Missing1516152
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean0.02656106438
Minimum0
Maximum166.666667
Zeros441
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:51.183753image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3e-05
median0.000104
Q30.0002
95-th percentile0.000488
Maximum166.666667
Range166.666667
Interquartile range (IQR)0.000167

Descriptive statistics

Standard deviation1.864973889
Coefficient of variation (CV)70.2145766
Kurtosis7588.760911
Mean0.02656106438
Median Absolute Deviation (MAD)7.5e-05
Skewness85.72656433
Sum223.8300895
Variance3.478127607
MonotocityNot monotonic
2020-12-04T09:39:51.325147image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.000214702< 0.1%
 
0441< 0.1%
 
0.000179396< 0.1%
 
2.9e-05203< 0.1%
 
2.5e-05200< 0.1%
 
0.000133186< 0.1%
 
7.7e-05184< 0.1%
 
1.7e-05150< 0.1%
 
4.2e-05142< 0.1%
 
0.000667125< 0.1%
 
Other values (408)56980.4%
 
(Missing)151615299.4%
 
ValueCountFrequency (%) 
0441< 0.1%
 
1e-0627< 0.1%
 
2e-0627< 0.1%
 
3e-0652< 0.1%
 
3.39e-061< 0.1%
 
ValueCountFrequency (%) 
166.6666671< 0.1%
 
38.46151< 0.1%
 
3.846151< 0.1%
 
3.448282< 0.1%
 
3.333331< 0.1%
 

vitamin-b12_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct777
Distinct (%)6.3%
Missing1512258
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean0.01580730572
Minimum0
Maximum65.7895
Zeros1218
Zeros (%)0.1%
Memory size11.6 MiB
2020-12-04T09:39:51.467501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14e-07
median1.5e-06
Q34e-06
95-th percentile2e-05
Maximum65.7895
Range65.7895
Interquartile range (IQR)3.6e-06

Descriptive statistics

Standard deviation0.7051836796
Coefficient of variation (CV)44.61125077
Kurtosis6518.683174
Mean0.01580730572
Median Absolute Deviation (MAD)1.18e-06
Skewness75.70509683
Sum194.7618138
Variance0.497284022
MonotocityNot monotonic
2020-12-04T09:39:51.626186image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
012180.1%
 
2.5e-07417< 0.1%
 
5e-06417< 0.1%
 
3.8e-07400< 0.1%
 
2.5e-06376< 0.1%
 
5e-07261< 0.1%
 
1.25e-06231< 0.1%
 
2.1e-06229< 0.1%
 
3e-05198< 0.1%
 
4e-07191< 0.1%
 
Other values (767)83830.5%
 
(Missing)151225899.2%
 
ValueCountFrequency (%) 
012180.1%
 
1e-101< 0.1%
 
4e-101< 0.1%
 
5e-102< 0.1%
 
9e-101< 0.1%
 
ValueCountFrequency (%) 
65.78951< 0.1%
 
311< 0.1%
 
201< 0.1%
 
151< 0.1%
 
10.31< 0.1%
 

biotin_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct230
Distinct (%)23.7%
Missing1523610
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean0.2527274914
Minimum0
Maximum100
Zeros11
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:51.819657image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1e-06
Q15e-06
median1.5e-05
Q34.15e-05
95-th percentile0.0016312
Maximum100
Range100
Interquartile range (IQR)3.65e-05

Descriptive statistics

Standard deviation3.718102825
Coefficient of variation (CV)14.71190492
Kurtosis556.024398
Mean0.2527274914
Median Absolute Deviation (MAD)1.27e-05
Skewness22.1109395
Sum244.8929392
Variance13.82428862
MonotocityNot monotonic
2020-12-04T09:39:51.953081image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7.5e-06100< 0.1%
 
1e-0657< 0.1%
 
5e-0543< 0.1%
 
2e-0533< 0.1%
 
1e-0532< 0.1%
 
4.15e-0530< 0.1%
 
1.5e-0529< 0.1%
 
3e-0627< 0.1%
 
3e-0524< 0.1%
 
2e-0619< 0.1%
 
Other values (220)575< 0.1%
 
(Missing)152361099.9%
 
ValueCountFrequency (%) 
011< 0.1%
 
2e-091< 0.1%
 
1e-0657< 0.1%
 
1.2e-062< 0.1%
 
1.3e-062< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
421< 0.1%
 
281< 0.1%
 
153< 0.1%
 
101< 0.1%
 

pantothenic-acid_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct798
Distinct (%)13.6%
Missing1518705
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean0.04341049497
Minimum0
Maximum50
Zeros153
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:52.082743image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.000169
Q10.00067275
median0.001639
Q30.0038
95-th percentile0.016667
Maximum50
Range50
Interquartile range (IQR)0.00312725

Descriptive statistics

Standard deviation0.8633150986
Coefficient of variation (CV)19.88724384
Kurtosis2075.515413
Mean0.04341049497
Median Absolute Deviation (MAD)0.001222
Skewness40.94662316
Sum254.9932474
Variance0.7453129594
MonotocityNot monotonic
2020-12-04T09:39:52.221913image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.000417298< 0.1%
 
0.002239< 0.1%
 
0.001429171< 0.1%
 
0153< 0.1%
 
0.0009152< 0.1%
 
0.001042137< 0.1%
 
0.004167125< 0.1%
 
0.006113< 0.1%
 
0.005107< 0.1%
 
0.00105588< 0.1%
 
Other values (788)42910.3%
 
(Missing)151870599.6%
 
ValueCountFrequency (%) 
0153< 0.1%
 
3.2e-091< 0.1%
 
5.1e-091< 0.1%
 
7e-091< 0.1%
 
3e-071< 0.1%
 
ValueCountFrequency (%) 
501< 0.1%
 
22.91< 0.1%
 
16.92051< 0.1%
 
16.1291< 0.1%
 
161< 0.1%
 

silica_100g
Real number (ℝ≥0)

MISSING

Distinct69
Distinct (%)62.2%
Missing1524468
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.04811427117
Minimum0
Maximum1.54
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:52.357291image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00048
Q10.0015
median0.0035
Q30.015
95-th percentile0.0935
Maximum1.54
Range1.54
Interquartile range (IQR)0.0135

Descriptive statistics

Standard deviation0.2102441262
Coefficient of variation (CV)4.369683278
Kurtosis43.38550908
Mean0.04811427117
Median Absolute Deviation (MAD)0.00279
Skewness6.487145498
Sum5.3406841
Variance0.0442025926
MonotocityNot monotonic
2020-12-04T09:39:52.483307image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.00159< 0.1%
 
0.000715< 0.1%
 
0.0155< 0.1%
 
0.00715< 0.1%
 
0.00354< 0.1%
 
0.0323< 0.1%
 
0.003173< 0.1%
 
0.003273< 0.1%
 
0.0273< 0.1%
 
0.00092< 0.1%
 
Other values (59)69< 0.1%
 
(Missing)1524468> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
7.9e-061< 0.1%
 
8.2e-061< 0.1%
 
2.6e-051< 0.1%
 
9.7e-051< 0.1%
 
ValueCountFrequency (%) 
1.541< 0.1%
 
1.51< 0.1%
 
0.5251< 0.1%
 
0.3271< 0.1%
 
0.251< 0.1%
 

bicarbonate_100g
Real number (ℝ≥0)

MISSING

Distinct253
Distinct (%)70.1%
Missing1524218
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.9668324042
Minimum0
Maximum100
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:52.624171image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00084
Q10.0183
median0.0431
Q30.215
95-th percentile1.3005
Maximum100
Range100
Interquartile range (IQR)0.1967

Descriptive statistics

Standard deviation7.505128873
Coefficient of variation (CV)7.762595504
Kurtosis146.8386567
Mean0.9668324042
Median Absolute Deviation (MAD)0.0401
Skewness11.84052534
Sum349.0264979
Variance56.3269594
MonotocityNot monotonic
2020-12-04T09:39:52.761563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0369< 0.1%
 
0.366< 0.1%
 
0.0155< 0.1%
 
0.01355< 0.1%
 
0.01734< 0.1%
 
0.1354< 0.1%
 
0.154< 0.1%
 
0.02594< 0.1%
 
0.2983< 0.1%
 
0.4373< 0.1%
 
Other values (243)314< 0.1%
 
(Missing)1524218> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
6.3e-061< 0.1%
 
3.21e-051< 0.1%
 
0.0001191< 0.1%
 
0.0002441< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
92.61< 0.1%
 
361< 0.1%
 
201< 0.1%
 
10.31< 0.1%
 

potassium_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct2034
Distinct (%)2.2%
Missing1433088
Missing (%)94.0%
Infinite0
Infinite (%)0.0%
Mean0.4166607402
Minimum0
Maximum696
Zeros8859
Zeros (%)0.6%
Memory size11.6 MiB
2020-12-04T09:39:52.899948image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.08
median0.167
Q30.3
95-th percentile0.857
Maximum696
Range696
Interquartile range (IQR)0.22

Descriptive statistics

Standard deviation6.716673021
Coefficient of variation (CV)16.12024454
Kurtosis5232.982993
Mean0.4166607402
Median Absolute Deviation (MAD)0.098
Skewness66.35740207
Sum38120.70778
Variance45.11369646
MonotocityNot monotonic
2020-12-04T09:39:53.029370image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
088590.6%
 
0.18811680.1%
 
0.110240.1%
 
0.07110200.1%
 
0.28850.1%
 
0.1677900.1%
 
0.133735< 0.1%
 
0.25730< 0.1%
 
0.15650< 0.1%
 
0.125633< 0.1%
 
Other values (2024)749974.9%
 
(Missing)143308894.0%
 
ValueCountFrequency (%) 
088590.6%
 
2.74e-071< 0.1%
 
4e-071< 0.1%
 
6.95e-071< 0.1%
 
9e-071< 0.1%
 
ValueCountFrequency (%) 
6961< 0.1%
 
6621< 0.1%
 
6001< 0.1%
 
5621< 0.1%
 
5251< 0.1%
 

chloride_100g
Real number (ℝ≥0)

MISSING

Distinct322
Distinct (%)49.8%
Missing1523932
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.3339915102
Minimum0
Maximum80
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:53.168284image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00012
Q10.0012
median0.0069
Q30.054
95-th percentile0.3835
Maximum80
Range80
Interquartile range (IQR)0.0528

Descriptive statistics

Standard deviation3.906094547
Coefficient of variation (CV)11.69519113
Kurtosis314.2650803
Mean0.3339915102
Median Absolute Deviation (MAD)0.00668
Skewness17.13332065
Sum216.0925071
Variance15.25757461
MonotocityNot monotonic
2020-12-04T09:39:53.305642image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.09525< 0.1%
 
0.00120< 0.1%
 
0.000511< 0.1%
 
0.0511< 0.1%
 
0.000110< 0.1%
 
0.001210< 0.1%
 
0.068< 0.1%
 
0.0548< 0.1%
 
0.0098< 0.1%
 
0.00228< 0.1%
 
Other values (312)528< 0.1%
 
(Missing)1523932> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
3e-061< 0.1%
 
4.3e-061< 0.1%
 
5e-061< 0.1%
 
1.1e-051< 0.1%
 
ValueCountFrequency (%) 
801< 0.1%
 
501< 0.1%
 
31.21< 0.1%
 
3.27761< 0.1%
 
31< 0.1%
 

calcium_100g
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct2086
Distinct (%)0.8%
Missing1255649
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean0.1676109529
Minimum0
Maximum930
Zeros84863
Zeros (%)5.6%
Memory size11.6 MiB
2020-12-04T09:39:53.457914image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.036
Q30.109
95-th percentile0.471
Maximum930
Range930
Interquartile range (IQR)0.109

Descriptive statistics

Standard deviation4.683791549
Coefficient of variation (CV)27.94442409
Kurtosis16697.11313
Mean0.1676109529
Median Absolute Deviation (MAD)0.036
Skewness116.1701179
Sum45075.61356
Variance21.93790327
MonotocityNot monotonic
2020-12-04T09:39:53.592355image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0848635.6%
 
0.07185740.6%
 
0.06750080.3%
 
0.71440490.3%
 
0.138390.3%
 
0.03635590.2%
 
0.13335400.2%
 
0.02434100.2%
 
0.14331930.2%
 
0.01831740.2%
 
Other values (2076)1457219.6%
 
(Missing)125564982.4%
 
ValueCountFrequency (%) 
0848635.6%
 
1e-101< 0.1%
 
2e-101< 0.1%
 
3e-101< 0.1%
 
2.8e-081< 0.1%
 
ValueCountFrequency (%) 
9301< 0.1%
 
7791< 0.1%
 
7001< 0.1%
 
6671< 0.1%
 
613.6361< 0.1%
 

phosphorus_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct924
Distinct (%)6.8%
Missing1511077
Missing (%)99.1%
Infinite0
Infinite (%)0.0%
Mean0.5429505097
Minimum0
Maximum559.459
Zeros125
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:53.725787image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.008
Q10.088
median0.182
Q30.333
95-th percentile0.625
Maximum559.459
Range559.459
Interquartile range (IQR)0.245

Descriptive statistics

Standard deviation8.685309152
Coefficient of variation (CV)15.99650244
Kurtosis2064.821469
Mean0.5429505097
Median Absolute Deviation (MAD)0.105
Skewness41.58629645
Sum7330.917782
Variance75.43459506
MonotocityNot monotonic
2020-12-04T09:39:53.855740image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.357452< 0.1%
 
0.143385< 0.1%
 
0.008363< 0.1%
 
0.536344< 0.1%
 
0.088342< 0.1%
 
0.286270< 0.1%
 
0.2255< 0.1%
 
0.25205< 0.1%
 
0.104203< 0.1%
 
0.333193< 0.1%
 
Other values (914)104900.7%
 
(Missing)151107799.1%
 
ValueCountFrequency (%) 
0125< 0.1%
 
1.8e-071< 0.1%
 
1.96e-071< 0.1%
 
2.3e-071< 0.1%
 
2.57e-071< 0.1%
 
ValueCountFrequency (%) 
559.4591< 0.1%
 
410.871< 0.1%
 
3201< 0.1%
 
315.5561< 0.1%
 
2711< 0.1%
 

iron_100g
Real number (ℝ)

MISSING
SKEWED
ZEROS

Distinct1845
Distinct (%)0.7%
Missing1260498
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.006745758727
Minimum-0.00026
Maximum100
Zeros79661
Zeros (%)5.2%
Memory size11.6 MiB
2020-12-04T09:39:53.995616image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.00026
5-th percentile0
Q10
median0.001
Q30.0024
95-th percentile0.006
Maximum100
Range100.00026
Interquartile range (IQR)0.0024

Descriptive statistics

Standard deviation0.3258861545
Coefficient of variation (CV)48.3097851
Kurtosis40579.32131
Mean0.006745758727
Median Absolute Deviation (MAD)0.001
Skewness167.5003907
Sum1781.426711
Variance0.1062017857
MonotocityNot monotonic
2020-12-04T09:39:54.128544image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0796615.2%
 
0.0012991030.6%
 
0.0025756800.4%
 
0.0006436420.2%
 
0.002435830.2%
 
0.003634740.2%
 
0.001231680.2%
 
0.0038628100.2%
 
0.0032125680.2%
 
0.001823150.2%
 
Other values (1835)1480779.7%
 
(Missing)126049882.7%
 
ValueCountFrequency (%) 
-0.000261< 0.1%
 
0796615.2%
 
2.6e-091< 0.1%
 
3.3e-091< 0.1%
 
4.7e-091< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
501< 0.1%
 
48.91< 0.1%
 
45.21< 0.1%
 
35.21< 0.1%
 

magnesium_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct1145
Distinct (%)7.9%
Missing1510148
Missing (%)99.1%
Infinite0
Infinite (%)0.0%
Mean0.3593047155
Minimum0
Maximum506
Zeros234
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:54.263455image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.002
Q10.017
median0.059
Q30.133
95-th percentile0.3
Maximum506
Range506
Interquartile range (IQR)0.116

Descriptive statistics

Standard deviation6.864981192
Coefficient of variation (CV)19.10629306
Kurtosis3032.169642
Mean0.3593047155
Median Absolute Deviation (MAD)0.049
Skewness49.72523335
Sum5185.126349
Variance47.12796676
MonotocityNot monotonic
2020-12-04T09:39:54.402342image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.01524< 0.1%
 
0.007424< 0.1%
 
0.143362< 0.1%
 
0.057349< 0.1%
 
0.286316< 0.1%
 
0.016235< 0.1%
 
0234< 0.1%
 
0.024228< 0.1%
 
0.214218< 0.1%
 
0.017206< 0.1%
 
Other values (1135)113350.7%
 
(Missing)151014899.1%
 
ValueCountFrequency (%) 
0234< 0.1%
 
7.75e-081< 0.1%
 
1.1e-071< 0.1%
 
1.49e-071< 0.1%
 
5e-072< 0.1%
 
ValueCountFrequency (%) 
5061< 0.1%
 
364.2861< 0.1%
 
333.3331< 0.1%
 
1681< 0.1%
 
1351< 0.1%
 

zinc_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct763
Distinct (%)7.6%
Missing1514575
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean0.0256094285
Minimum0
Maximum42
Zeros228
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:54.541211image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0002
Q10.00091
median0.00273
Q30.0058825
95-th percentile0.01389
Maximum42
Range42
Interquartile range (IQR)0.0049725

Descriptive statistics

Standard deviation0.6403883678
Coefficient of variation (CV)25.0059609
Kurtosis3413.481471
Mean0.0256094285
Median Absolute Deviation (MAD)0.00213
Skewness55.17629642
Sum256.1967227
Variance0.4100972617
MonotocityNot monotonic
2020-12-04T09:39:54.664714image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0005268< 0.1%
 
0.00536245< 0.1%
 
0.0125245< 0.1%
 
0228< 0.1%
 
0.0002222< 0.1%
 
0.0004213< 0.1%
 
0.005202< 0.1%
 
0.00107181< 0.1%
 
0.0015159< 0.1%
 
0.0006153< 0.1%
 
Other values (753)78880.5%
 
(Missing)151457599.3%
 
ValueCountFrequency (%) 
0228< 0.1%
 
2.5e-091< 0.1%
 
8.4e-091< 0.1%
 
9.3e-091< 0.1%
 
6e-071< 0.1%
 
ValueCountFrequency (%) 
421< 0.1%
 
401< 0.1%
 
151< 0.1%
 
131< 0.1%
 
7.31< 0.1%
 

copper_100g
Real number (ℝ)

MISSING
SKEWED

Distinct506
Distinct (%)12.0%
Missing1520367
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean0.02179258138
Minimum-6.896552
Maximum69
Zeros42
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:54.834843image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-6.896552
5-th percentile4.5e-05
Q10.0002
median0.000429
Q30.001071
95-th percentile0.002143
Maximum69
Range75.896552
Interquartile range (IQR)0.000871

Descriptive statistics

Standard deviation1.101386699
Coefficient of variation (CV)50.5395244
Kurtosis3668.016517
Mean0.02179258138
Median Absolute Deviation (MAD)0.000308
Skewness59.12314678
Sum91.79035279
Variance1.21305266
MonotocityNot monotonic
2020-12-04T09:39:54.968787image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.001071226< 0.1%
 
0.001429161< 0.1%
 
0.001147< 0.1%
 
0.000571132< 0.1%
 
0.002143123< 0.1%
 
5.4e-05120< 0.1%
 
0.00013395< 0.1%
 
0.00020885< 0.1%
 
0.00071481< 0.1%
 
0.00036478< 0.1%
 
Other values (496)29640.2%
 
(Missing)152036799.7%
 
ValueCountFrequency (%) 
-6.8965521< 0.1%
 
042< 0.1%
 
1.4e-071< 0.1%
 
2e-071< 0.1%
 
3.5e-071< 0.1%
 
ValueCountFrequency (%) 
691< 0.1%
 
16.48351< 0.1%
 
5.2631581< 0.1%
 
0.91< 0.1%
 
0.511< 0.1%
 

manganese_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct235
Distinct (%)5.9%
Missing1520609
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean0.006396060003
Minimum0
Maximum5.6
Zeros1317
Zeros (%)0.1%
Memory size11.6 MiB
2020-12-04T09:39:55.117070image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.001
Q30.002
95-th percentile0.004
Maximum5.6
Range5.6
Interquartile range (IQR)0.002

Descriptive statistics

Standard deviation0.1113438779
Coefficient of variation (CV)17.40819784
Kurtosis1704.866764
Mean0.006396060003
Median Absolute Deviation (MAD)0.001
Skewness37.61503426
Sum25.39235821
Variance0.01239745915
MonotocityNot monotonic
2020-12-04T09:39:55.242041image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
013170.1%
 
0.0029860.1%
 
0.0017760.1%
 
0.003194< 0.1%
 
0.004111< 0.1%
 
0.00545< 0.1%
 
0.00625< 0.1%
 
0.000217< 0.1%
 
0.00813< 0.1%
 
0.000313< 0.1%
 
Other values (225)473< 0.1%
 
(Missing)152060999.7%
 
ValueCountFrequency (%) 
013170.1%
 
1e-064< 0.1%
 
1.9e-061< 0.1%
 
2.7e-061< 0.1%
 
3e-065< 0.1%
 
ValueCountFrequency (%) 
5.61< 0.1%
 
2.471< 0.1%
 
1.841< 0.1%
 
1.651< 0.1%
 
1.31< 0.1%
 

fluoride_100g
Real number (ℝ≥0)

MISSING

Distinct107
Distinct (%)35.1%
Missing1524274
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.06485409393
Minimum1e-07
Maximum17
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:55.478719image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1e-07
5-th percentile5e-06
Q11.5e-05
median6.6e-05
Q30.0004
95-th percentile0.031
Maximum17
Range16.9999999
Interquartile range (IQR)0.000385

Descriptive statistics

Standard deviation0.9743932828
Coefficient of variation (CV)15.02439127
Kurtosis303.1083393
Mean0.06485409393
Median Absolute Deviation (MAD)5.6e-05
Skewness17.38469631
Sum19.78049865
Variance0.9494422696
MonotocityNot monotonic
2020-12-04T09:39:55.656286image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1e-0536< 0.1%
 
1.5e-0516< 0.1%
 
0.03114< 0.1%
 
5e-0513< 0.1%
 
0.000112< 0.1%
 
2e-0512< 0.1%
 
0.0001210< 0.1%
 
0.00059< 0.1%
 
0.0258< 0.1%
 
5e-067< 0.1%
 
Other values (97)168< 0.1%
 
(Missing)1524274> 99.9%
 
ValueCountFrequency (%) 
1e-071< 0.1%
 
2e-071< 0.1%
 
2.8e-071< 0.1%
 
3e-071< 0.1%
 
5.2e-071< 0.1%
 
ValueCountFrequency (%) 
171< 0.1%
 
0.561< 0.1%
 
0.5041< 0.1%
 
0.4991< 0.1%
 
0.231< 0.1%
 

selenium_100g
Real number (ℝ)

MISSING
SKEWED

Distinct265
Distinct (%)11.0%
Missing1522177
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean0.1178462599
Minimum-2e-06
Maximum230
Zeros46
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:55.818510image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2e-06
5-th percentile1.5e-06
Q15e-06
median1.6e-05
Q34.5e-05
95-th percentile0.000112
Maximum230
Range230.000002
Interquartile range (IQR)4e-05

Descriptive statistics

Standard deviation4.733155682
Coefficient of variation (CV)40.16381755
Kurtosis2320.682726
Mean0.1178462599
Median Absolute Deviation (MAD)1.3e-05
Skewness47.83093667
Sum283.0667163
Variance22.40276271
MonotocityNot monotonic
2020-12-04T09:39:56.001502image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7e-06148< 0.1%
 
4e-06132< 0.1%
 
5e-06128< 0.1%
 
3e-06102< 0.1%
 
2e-0677< 0.1%
 
2.1e-0576< 0.1%
 
3e-0572< 0.1%
 
8e-0668< 0.1%
 
1e-0563< 0.1%
 
9e-0659< 0.1%
 
Other values (255)14770.1%
 
(Missing)152217799.8%
 
ValueCountFrequency (%) 
-2e-061< 0.1%
 
046< 0.1%
 
2.5e-082< 0.1%
 
2.9e-081< 0.1%
 
7e-078< 0.1%
 
ValueCountFrequency (%) 
2301< 0.1%
 
251< 0.1%
 
13.91< 0.1%
 
9.71< 0.1%
 
2.81< 0.1%
 

chromium_100g
Real number (ℝ≥0)

MISSING

Distinct81
Distinct (%)47.4%
Missing1524408
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.628408428
Minimum0
Maximum99
Zeros3
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:56.262894image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2e-06
Q17.2e-06
median1.2e-05
Q35.9e-05
95-th percentile0.00179
Maximum99
Range99
Interquartile range (IQR)5.18e-05

Descriptive statistics

Standard deviation7.591649287
Coefficient of variation (CV)12.08075664
Kurtosis168.7481231
Mean0.628408428
Median Absolute Deviation (MAD)8e-06
Skewness12.9546264
Sum107.4578412
Variance57.6331389
MonotocityNot monotonic
2020-12-04T09:39:56.472207image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.4e-0511< 0.1%
 
4e-0610< 0.1%
 
1.2e-059< 0.1%
 
8e-069< 0.1%
 
1e-059< 0.1%
 
3e-066< 0.1%
 
5e-066< 0.1%
 
6e-065< 0.1%
 
8.2e-065< 0.1%
 
1.3e-054< 0.1%
 
Other values (71)97< 0.1%
 
(Missing)1524408> 99.9%
 
ValueCountFrequency (%) 
03< 0.1%
 
5e-071< 0.1%
 
1e-061< 0.1%
 
1.76e-061< 0.1%
 
1.86e-061< 0.1%
 
ValueCountFrequency (%) 
991< 0.1%
 
81< 0.1%
 
0.41< 0.1%
 
0.031< 0.1%
 
0.011< 0.1%
 

molybdenum_100g
Real number (ℝ≥0)

MISSING

Distinct86
Distinct (%)37.9%
Missing1524352
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.1007475689
Minimum0
Maximum18.8
Zeros5
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:56.667631image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3e-06
Q15.9e-06
median1.6e-05
Q34.3e-05
95-th percentile0.00024
Maximum18.8
Range18.8
Interquartile range (IQR)3.71e-05

Descriptive statistics

Standard deviation1.27455954
Coefficient of variation (CV)12.6510203
Kurtosis207.8704712
Mean0.1007475689
Median Absolute Deviation (MAD)1.13e-05
Skewness14.22434539
Sum22.86969815
Variance1.624502021
MonotocityNot monotonic
2020-12-04T09:39:56.861104image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
4.7e-0625< 0.1%
 
7e-0613< 0.1%
 
1.6e-0512< 0.1%
 
2.9e-059< 0.1%
 
1.5e-058< 0.1%
 
3e-068< 0.1%
 
5e-067< 0.1%
 
1.2e-057< 0.1%
 
1.1e-056< 0.1%
 
6e-066< 0.1%
 
Other values (76)126< 0.1%
 
(Missing)1524352> 99.9%
 
ValueCountFrequency (%) 
05< 0.1%
 
2e-061< 0.1%
 
2.2e-061< 0.1%
 
2.5e-063< 0.1%
 
3e-068< 0.1%
 
ValueCountFrequency (%) 
18.81< 0.1%
 
41< 0.1%
 
0.0357141< 0.1%
 
0.01381< 0.1%
 
0.0052< 0.1%
 

iodine_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct366
Distinct (%)18.2%
Missing1522568
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean0.1706383103
Minimum0
Maximum91
Zeros24
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:57.062482image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9e-06
Q11.3e-05
median2.2e-05
Q37.575e-05
95-th percentile0.004467
Maximum91
Range91
Interquartile range (IQR)6.275e-05

Descriptive statistics

Standard deviation2.72645537
Coefficient of variation (CV)15.97797919
Kurtosis676.7652376
Mean0.1706383103
Median Absolute Deviation (MAD)1.3e-05
Skewness23.5446205
Sum343.153642
Variance7.433558886
MonotocityNot monotonic
2020-12-04T09:39:57.289119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.6e-05238< 0.1%
 
1.1e-05139< 0.1%
 
9e-06104< 0.1%
 
1.2e-0582< 0.1%
 
1.5e-0569< 0.1%
 
4.5e-0563< 0.1%
 
2.2e-0544< 0.1%
 
1e-0536< 0.1%
 
0.004535< 0.1%
 
1.8e-0535< 0.1%
 
Other values (356)11660.1%
 
(Missing)152256899.9%
 
ValueCountFrequency (%) 
024< 0.1%
 
3.6e-091< 0.1%
 
3.8e-091< 0.1%
 
2.25e-081< 0.1%
 
1.8e-071< 0.1%
 
ValueCountFrequency (%) 
911< 0.1%
 
44.61< 0.1%
 
311< 0.1%
 
29.71< 0.1%
 
291< 0.1%
 

caffeine_100g
Real number (ℝ≥0)

MISSING

Distinct133
Distinct (%)34.2%
Missing1524190
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1.285060391
Minimum0
Maximum100
Zeros22
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:57.447839image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.017
median0.032
Q30.045
95-th percentile2.98
Maximum100
Range100
Interquartile range (IQR)0.028

Descriptive statistics

Standard deviation7.805096777
Coefficient of variation (CV)6.073719829
Kurtosis96.96286077
Mean1.285060391
Median Absolute Deviation (MAD)0.014
Skewness9.192343356
Sum499.888492
Variance60.9195357
MonotocityNot monotonic
2020-12-04T09:39:57.602592image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.03264< 0.1%
 
0.0335< 0.1%
 
022< 0.1%
 
0.00418< 0.1%
 
0.0216< 0.1%
 
0.048< 0.1%
 
0.0187< 0.1%
 
0.0217< 0.1%
 
0.0066< 0.1%
 
26< 0.1%
 
Other values (123)200< 0.1%
 
(Missing)1524190> 99.9%
 
ValueCountFrequency (%) 
022< 0.1%
 
3.2e-051< 0.1%
 
0.0023< 0.1%
 
0.0032< 0.1%
 
0.00418< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
801< 0.1%
 
42.281< 0.1%
 
401< 0.1%
 
351< 0.1%
 

taurine_100g
Real number (ℝ≥0)

MISSING

Distinct50
Distinct (%)35.7%
Missing1524439
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3.569524071
Minimum0.00035
Maximum400
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:39:57.749936image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.00035
5-th percentile0.014465
Q10.039875
median0.4
Q30.4
95-th percentile2
Maximum400
Range399.99965
Interquartile range (IQR)0.360125

Descriptive statistics

Standard deviation33.87539787
Coefficient of variation (CV)9.490172133
Kurtosis137.8230345
Mean3.569524071
Median Absolute Deviation (MAD)0.0985
Skewness11.7011919
Sum499.73337
Variance1147.542581
MonotocityNot monotonic
2020-12-04T09:39:57.892282image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.457< 0.1%
 
0.0365< 0.1%
 
0.0355< 0.1%
 
0.244< 0.1%
 
0.043< 0.1%
 
0.053< 0.1%
 
0.123< 0.1%
 
23< 0.1%
 
0.353< 0.1%
 
0.0393< 0.1%
 
Other values (40)51< 0.1%
 
(Missing)1524439> 99.9%
 
ValueCountFrequency (%) 
0.000351< 0.1%
 
0.000721< 0.1%
 
0.00181< 0.1%
 
0.00331< 0.1%
 
0.00532< 0.1%
 
ValueCountFrequency (%) 
4001< 0.1%
 
331< 0.1%
 
11.21< 0.1%
 
5.541< 0.1%
 
31< 0.1%
 

ph_100g
Real number (ℝ≥0)

MISSING

Distinct63
Distinct (%)37.3%
Missing1524410
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean6.759821266
Minimum0
Maximum14
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:58.046051image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.74
Q16.1
median7.2
Q37.6
95-th percentile8
Maximum14
Range14
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.648506901
Coefficient of variation (CV)0.2438684155
Kurtosis9.89959272
Mean6.759821266
Median Absolute Deviation (MAD)0.5
Skewness-1.98419065
Sum1142.409794
Variance2.717575003
MonotocityNot monotonic
2020-12-04T09:39:58.181425image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7.516< 0.1%
 
7.216< 0.1%
 
614< 0.1%
 
7.610< 0.1%
 
79< 0.1%
 
7.78< 0.1%
 
7.87< 0.1%
 
7.37< 0.1%
 
86< 0.1%
 
6.66< 0.1%
 
Other values (53)70< 0.1%
 
(Missing)1524410> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.0051< 0.1%
 
0.00581< 0.1%
 
0.00641< 0.1%
 
0.00651< 0.1%
 
ValueCountFrequency (%) 
141< 0.1%
 
9.41< 0.1%
 
8.41< 0.1%
 
8.31< 0.1%
 
8.21< 0.1%
 

fruits-vegetables-nuts_100g
Real number (ℝ≥0)

MISSING

Distinct1103
Distinct (%)13.0%
Missing1516062
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean34.20983339
Minimum0
Maximum100
Zeros2725
Zeros (%)0.2%
Memory size11.6 MiB
2020-12-04T09:39:58.383796image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20.82
Q360
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)60

Descriptive statistics

Standard deviation36.48404425
Coefficient of variation (CV)1.066478279
Kurtosis-0.9828864167
Mean34.20983339
Median Absolute Deviation (MAD)20.82
Skewness0.6887172068
Sum291365.151
Variance1331.085485
MonotocityNot monotonic
2020-12-04T09:39:59.366370image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
027250.2%
 
1009300.1%
 
50458< 0.1%
 
55141< 0.1%
 
40130< 0.1%
 
25126< 0.1%
 
12116< 0.1%
 
60107< 0.1%
 
1099< 0.1%
 
3081< 0.1%
 
Other values (1093)36040.2%
 
(Missing)151606299.4%
 
ValueCountFrequency (%) 
027250.2%
 
0.032< 0.1%
 
0.042< 0.1%
 
0.051< 0.1%
 
0.15< 0.1%
 
ValueCountFrequency (%) 
1009300.1%
 
99.991< 0.1%
 
99.9721< 0.1%
 
99.971< 0.1%
 
99.951< 0.1%
 

fruits-vegetables-nuts-dried_100g
Real number (ℝ≥0)

MISSING

Distinct90
Distinct (%)30.8%
Missing1524287
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean22.75282877
Minimum0
Maximum100
Zeros130
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:59.523601image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.9
Q341.25
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)41.25

Descriptive statistics

Standard deviation34.08849147
Coefficient of variation (CV)1.49820894
Kurtosis-0.00793795481
Mean22.75282877
Median Absolute Deviation (MAD)1.9
Skewness1.246540265
Sum6643.826
Variance1162.025251
MonotocityNot monotonic
2020-12-04T09:39:59.679346image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0130< 0.1%
 
10016< 0.1%
 
656< 0.1%
 
855< 0.1%
 
504< 0.1%
 
354< 0.1%
 
44< 0.1%
 
254< 0.1%
 
964< 0.1%
 
554< 0.1%
 
Other values (80)111< 0.1%
 
(Missing)1524287> 99.9%
 
ValueCountFrequency (%) 
0130< 0.1%
 
0.0061< 0.1%
 
0.0111< 0.1%
 
0.21< 0.1%
 
0.31< 0.1%
 
ValueCountFrequency (%) 
10016< 0.1%
 
981< 0.1%
 
973< 0.1%
 
964< 0.1%
 
951< 0.1%
 

fruits-vegetables-nuts-estimate_100g
Real number (ℝ≥0)

MISSING

Distinct838
Distinct (%)7.2%
Missing1512985
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean46.263931
Minimum0
Maximum100
Zeros133
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:39:59.844052image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q117.5
median50
Q364
95-th percentile99.9
Maximum100
Range100
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation28.70929539
Coefficient of variation (CV)0.6205546041
Kurtosis-0.9098543909
Mean46.263931
Median Absolute Deviation (MAD)20
Skewness0.121535103
Sum536384.016
Variance824.2236416
MonotocityNot monotonic
2020-12-04T09:39:59.992850image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5010860.1%
 
557720.1%
 
60691< 0.1%
 
100572< 0.1%
 
65401< 0.1%
 
70264< 0.1%
 
10256< 0.1%
 
45224< 0.1%
 
8194< 0.1%
 
75154< 0.1%
 
Other values (828)69800.5%
 
(Missing)151298599.2%
 
ValueCountFrequency (%) 
0133< 0.1%
 
0.112< 0.1%
 
0.21< 0.1%
 
0.34< 0.1%
 
0.42< 0.1%
 
ValueCountFrequency (%) 
100572< 0.1%
 
99.991< 0.1%
 
99.971< 0.1%
 
99.951< 0.1%
 
99.936< 0.1%
 

collagen-meat-protein-ratio_100g
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)3.6%
Missing1524272
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean15.19814984
Minimum0.8
Maximum100
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:40:00.123291image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile12
Q113.5
median15
Q315
95-th percentile25
Maximum100
Range99.2
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation5.907813142
Coefficient of variation (CV)0.3887192326
Kurtosis139.286937
Mean15.19814984
Median Absolute Deviation (MAD)0
Skewness9.891361125
Sum4665.832
Variance34.90225612
MonotocityNot monotonic
2020-12-04T09:40:00.237379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
15199< 0.1%
 
1272< 0.1%
 
2521< 0.1%
 
186< 0.1%
 
203< 0.1%
 
3.71< 0.1%
 
101< 0.1%
 
81< 0.1%
 
1.3321< 0.1%
 
1001< 0.1%
 
(Missing)1524272> 99.9%
 
ValueCountFrequency (%) 
0.81< 0.1%
 
1.3321< 0.1%
 
3.71< 0.1%
 
81< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
1001< 0.1%
 
2521< 0.1%
 
203< 0.1%
 
186< 0.1%
 
15199< 0.1%
 

cocoa_100g
Real number (ℝ≥0)

MISSING

Distinct352
Distinct (%)6.2%
Missing1518915
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean51.57660584
Minimum0
Maximum100
Zeros14
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:40:00.371298image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.5
Q132
median52
Q370
95-th percentile85
Maximum100
Range100
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.84555552
Coefficient of variation (CV)0.4429441439
Kurtosis-0.670459752
Mean51.57660584
Median Absolute Deviation (MAD)19
Skewness-0.09209930512
Sum292129.8955
Variance521.919407
MonotocityNot monotonic
2020-12-04T09:40:00.525028image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
70601< 0.1%
 
30471< 0.1%
 
72269< 0.1%
 
85209< 0.1%
 
50187< 0.1%
 
60184< 0.1%
 
55164< 0.1%
 
32163< 0.1%
 
75139< 0.1%
 
33135< 0.1%
 
Other values (342)31420.2%
 
(Missing)151891599.6%
 
ValueCountFrequency (%) 
014< 0.1%
 
0.12< 0.1%
 
0.31< 0.1%
 
0.41< 0.1%
 
0.4841< 0.1%
 
ValueCountFrequency (%) 
100121< 0.1%
 
9926< 0.1%
 
984< 0.1%
 
9514< 0.1%
 
941< 0.1%
 

chlorophyl_100g
Categorical

MISSING

Distinct3
Distinct (%)100.0%
Missing1524576
Missing (%)> 99.9%
Memory size11.6 MiB
1.59
1 
1.575
1 
0.19915
1 
ValueCountFrequency (%) 
1.591< 0.1%
 
1.5751< 0.1%
 
0.199151< 0.1%
 
(Missing)1524576> 99.9%
 
2020-12-04T09:40:00.666386image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)100.0%

carbon-footprint_100g
Real number (ℝ≥0)

MISSING

Distinct228
Distinct (%)52.5%
Missing1524145
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean238.4331053
Minimum0
Maximum5000
Zeros139
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:40:00.793363image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median100
Q3280
95-th percentile1020.6
Maximum5000
Range5000
Interquartile range (IQR)280

Descriptive statistics

Standard deviation428.2949174
Coefficient of variation (CV)1.796289642
Kurtosis40.83645556
Mean238.4331053
Median Absolute Deviation (MAD)100
Skewness4.974957052
Sum103479.9677
Variance183436.5363
MonotocityNot monotonic
2020-12-04T09:40:00.947157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0139< 0.1%
 
10014< 0.1%
 
8285< 0.1%
 
1505< 0.1%
 
1534< 0.1%
 
1304< 0.1%
 
3654< 0.1%
 
3454< 0.1%
 
2004< 0.1%
 
3403< 0.1%
 
Other values (218)248< 0.1%
 
(Missing)1524145> 99.9%
 
ValueCountFrequency (%) 
0139< 0.1%
 
0.0111< 0.1%
 
0.052< 0.1%
 
0.21< 0.1%
 
0.71< 0.1%
 
ValueCountFrequency (%) 
50001< 0.1%
 
28421< 0.1%
 
25201< 0.1%
 
23801< 0.1%
 
14401< 0.1%
 

carbon-footprint-from-meat-or-fish_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct2515
Distinct (%)22.8%
Missing1513553
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean628.8545651
Minimum0.049
Maximum656298.6
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:40:01.102893image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.049
5-th percentile37.74
Q1111
median333
Q3614.2
95-th percentile2864
Maximum656298.6
Range656298.551
Interquartile range (IQR)503.2

Descriptive statistics

Standard deviation6307.248215
Coefficient of variation (CV)10.02974068
Kurtosis10595.45054
Mean628.8545651
Median Absolute Deviation (MAD)236.8
Skewness101.9364821
Sum6933750.435
Variance39781380.05
MonotocityNot monotonic
2020-12-04T09:40:01.238803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3580310< 0.1%
 
666158< 0.1%
 
630.5153< 0.1%
 
74103< 0.1%
 
680.873< 0.1%
 
88.871< 0.1%
 
11167< 0.1%
 
66.667< 0.1%
 
44165< 0.1%
 
96.264< 0.1%
 
Other values (2505)98950.6%
 
(Missing)151355399.3%
 
ValueCountFrequency (%) 
0.0492< 0.1%
 
0.1961< 0.1%
 
0.2051< 0.1%
 
0.2941< 0.1%
 
0.491< 0.1%
 
ValueCountFrequency (%) 
656298.61< 0.1%
 
358001< 0.1%
 
12232.21< 0.1%
 
107401< 0.1%
 
68021< 0.1%
 

nutrition-score-fr_100g
Real number (ℝ)

MISSING
ZEROS

Distinct55
Distinct (%)< 0.1%
Missing914694
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean9.148104971
Minimum-15
Maximum40
Zeros30887
Zeros (%)2.0%
Memory size11.6 MiB
2020-12-04T09:40:01.386109image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-15
5-th percentile-4
Q11
median10
Q316
95-th percentile24
Maximum40
Range55
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.907433701
Coefficient of variation (CV)0.9736916804
Kurtosis-0.955505093
Mean9.148104971
Median Absolute Deviation (MAD)7
Skewness0.08645060498
Sum5579292
Variance79.34237514
MonotocityNot monotonic
2020-12-04T09:40:01.526485image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
14316842.1%
 
0308872.0%
 
13269021.8%
 
11267711.8%
 
2259841.7%
 
15253921.7%
 
1250491.6%
 
3248171.6%
 
12246691.6%
 
16235311.5%
 
Other values (45)34419922.6%
 
(Missing)91469460.0%
 
ValueCountFrequency (%) 
-155< 0.1%
 
-1472< 0.1%
 
-13149< 0.1%
 
-12244< 0.1%
 
-11328< 0.1%
 
ValueCountFrequency (%) 
405< 0.1%
 
391< 0.1%
 
379< 0.1%
 
3627< 0.1%
 
3537< 0.1%
 

nutrition-score-uk_100g
Real number (ℝ)

MISSING

Distinct14
Distinct (%)56.0%
Missing1524554
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean8.16
Minimum-6
Maximum25
Zeros5
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:40:01.659875image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-6
5-th percentile-2.6
Q10
median5
Q317
95-th percentile20.8
Maximum25
Range31
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.463438417
Coefficient of variation (CV)1.1597351
Kurtosis-1.580800848
Mean8.16
Median Absolute Deviation (MAD)8
Skewness0.258011898
Sum204
Variance89.55666667
MonotocityNot monotonic
2020-12-04T09:40:01.762547image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
05< 0.1%
 
14< 0.1%
 
173< 0.1%
 
192< 0.1%
 
142< 0.1%
 
251< 0.1%
 
161< 0.1%
 
211< 0.1%
 
201< 0.1%
 
-11< 0.1%
 
Other values (4)4< 0.1%
 
(Missing)1524554> 99.9%
 
ValueCountFrequency (%) 
-61< 0.1%
 
-31< 0.1%
 
-11< 0.1%
 
05< 0.1%
 
14< 0.1%
 
ValueCountFrequency (%) 
251< 0.1%
 
211< 0.1%
 
201< 0.1%
 
192< 0.1%
 
173< 0.1%
 

glycemic-index_100g
Categorical

MISSING

Distinct3
Distinct (%)100.0%
Missing1524576
Missing (%)> 99.9%
Memory size11.6 MiB
30
1 
14
1 
44
1 
ValueCountFrequency (%) 
301< 0.1%
 
141< 0.1%
 
441< 0.1%
 
(Missing)1524576> 99.9%
 
2020-12-04T09:40:01.893988image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)100.0%

water-hardness_100g
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1524579
Missing (%)100.0%
Memory size11.6 MiB

choline_100g
Real number (ℝ≥0)

MISSING

Distinct26
Distinct (%)66.7%
Missing1524540
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.06645897436
Minimum0
Maximum0.15
Zeros1
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:40:02.013524image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0107
Q10.0475
median0.069
Q30.089
95-th percentile0.121
Maximum0.15
Range0.15
Interquartile range (IQR)0.0415

Descriptive statistics

Standard deviation0.03736696908
Coefficient of variation (CV)0.5622561804
Kurtosis-0.4731634343
Mean0.06645897436
Median Absolute Deviation (MAD)0.02
Skewness0.04115414624
Sum2.5919
Variance0.001396290378
MonotocityNot monotonic
2020-12-04T09:40:02.136036image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%) 
0.0696< 0.1%
 
0.064< 0.1%
 
0.1082< 0.1%
 
0.0892< 0.1%
 
0.0532< 0.1%
 
0.0112< 0.1%
 
0.1122< 0.1%
 
0.041< 0.1%
 
0.151< 0.1%
 
0.01531< 0.1%
 
Other values (16)16< 0.1%
 
(Missing)1524540> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.0081< 0.1%
 
0.0112< 0.1%
 
0.0121< 0.1%
 
0.0151< 0.1%
 
ValueCountFrequency (%) 
0.151< 0.1%
 
0.131< 0.1%
 
0.121< 0.1%
 
0.1161< 0.1%
 
0.1122< 0.1%
 

phylloquinone_100g
Real number (ℝ≥0)

MISSING
SKEWED

Distinct447
Distinct (%)26.1%
Missing1522867
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean0.0689202356
Minimum0
Maximum54
Zeros60
Zeros (%)< 0.1%
Memory size11.6 MiB
2020-12-04T09:40:02.285828image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.155e-06
Q18.3e-06
median2.35e-05
Q39.5475e-05
95-th percentile0.00060108
Maximum54
Range54
Interquartile range (IQR)8.7175e-05

Descriptive statistics

Standard deviation1.826776326
Coefficient of variation (CV)26.50565992
Kurtosis814.9047645
Mean0.0689202356
Median Absolute Deviation (MAD)1.79e-05
Skewness28.34559835
Sum117.9914434
Variance3.337111746
MonotocityNot monotonic
2020-12-04T09:40:02.441599image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
8.3e-0678< 0.1%
 
060< 0.1%
 
1.35e-0555< 0.1%
 
6.2e-0653< 0.1%
 
2.86e-0540< 0.1%
 
2.4e-0537< 0.1%
 
6.7e-0633< 0.1%
 
6.8e-0631< 0.1%
 
2.35e-0528< 0.1%
 
4.9e-0628< 0.1%
 
Other values (437)12690.1%
 
(Missing)152286799.9%
 
ValueCountFrequency (%) 
060< 0.1%
 
1e-071< 0.1%
 
7e-071< 0.1%
 
9e-071< 0.1%
 
1.2e-063< 0.1%
 
ValueCountFrequency (%) 
541< 0.1%
 
51.61< 0.1%
 
11.81< 0.1%
 
0.361< 0.1%
 
0.01714291< 0.1%
 

beta-glucan_100g
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)68.0%
Missing1524554
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3.5908
Minimum0.4
Maximum7.3
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:40:02.576522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile0.64
Q12.8
median3.9
Q34.4
95-th percentile5.38
Maximum7.3
Range6.9
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.630424076
Coefficient of variation (CV)0.4540559418
Kurtosis0.2915072442
Mean3.5908
Median Absolute Deviation (MAD)0.7
Skewness-0.2404926948
Sum89.77
Variance2.658282667
MonotocityNot monotonic
2020-12-04T09:40:02.685108image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
45< 0.1%
 
3.92< 0.1%
 
5.22< 0.1%
 
3.52< 0.1%
 
3.62< 0.1%
 
1.571< 0.1%
 
7.31< 0.1%
 
2.41< 0.1%
 
0.51< 0.1%
 
5.41< 0.1%
 
Other values (7)7< 0.1%
 
(Missing)1524554> 99.9%
 
ValueCountFrequency (%) 
0.41< 0.1%
 
0.51< 0.1%
 
1.21< 0.1%
 
1.51< 0.1%
 
1.571< 0.1%
 
ValueCountFrequency (%) 
7.31< 0.1%
 
5.41< 0.1%
 
5.31< 0.1%
 
5.22< 0.1%
 
4.61< 0.1%
 

inositol_100g
Real number (ℝ≥0)

MISSING

Distinct27
Distinct (%)61.4%
Missing1524535
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.02605613636
Minimum0.00135
Maximum0.15
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:40:02.814591image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.00135
5-th percentile0.002
Q10.00985
median0.021
Q30.0277
95-th percentile0.06525
Maximum0.15
Range0.14865
Interquartile range (IQR)0.01785

Descriptive statistics

Standard deviation0.02674510616
Coefficient of variation (CV)1.026441748
Kurtosis10.05930641
Mean0.02605613636
Median Absolute Deviation (MAD)0.0105
Skewness2.682963123
Sum1.14647
Variance0.0007153007033
MonotocityNot monotonic
2020-12-04T09:40:02.947495image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%) 
0.026< 0.1%
 
0.0255< 0.1%
 
0.0023< 0.1%
 
0.013< 0.1%
 
0.0243< 0.1%
 
0.00392< 0.1%
 
0.0612< 0.1%
 
0.0041< 0.1%
 
0.0661< 0.1%
 
0.00691< 0.1%
 
Other values (17)17< 0.1%
 
(Missing)1524535> 99.9%
 
ValueCountFrequency (%) 
0.001351< 0.1%
 
0.00161< 0.1%
 
0.0023< 0.1%
 
0.00392< 0.1%
 
0.0041< 0.1%
 
ValueCountFrequency (%) 
0.151< 0.1%
 
0.081< 0.1%
 
0.0661< 0.1%
 
0.0612< 0.1%
 
0.0551< 0.1%
 

carnitine_100g
Real number (ℝ≥0)

MISSING

Distinct12
Distinct (%)60.0%
Missing1524559
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean0.038885
Minimum0.004
Maximum0.572
Zeros0
Zeros (%)0.0%
Memory size11.6 MiB
2020-12-04T09:40:03.082901image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.004
5-th percentile0.006375
Q10.007
median0.0085
Q30.01125
95-th percentile0.0571
Maximum0.572
Range0.568
Interquartile range (IQR)0.00425

Descriptive statistics

Standard deviation0.1256787101
Coefficient of variation (CV)3.232061467
Kurtosis19.85408836
Mean0.038885
Median Absolute Deviation (MAD)0.002
Skewness4.449264277
Sum0.7777
Variance0.01579513818
MonotocityNot monotonic
2020-12-04T09:40:03.250053image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
0.00653< 0.1%
 
0.0113< 0.1%
 
0.032< 0.1%
 
0.00732< 0.1%
 
0.0072< 0.1%
 
0.00852< 0.1%
 
0.0121< 0.1%
 
0.00711< 0.1%
 
0.0151< 0.1%
 
0.00951< 0.1%
 
Other values (2)2< 0.1%
 
(Missing)1524559> 99.9%
 
ValueCountFrequency (%) 
0.0041< 0.1%
 
0.00653< 0.1%
 
0.0072< 0.1%
 
0.00711< 0.1%
 
0.00732< 0.1%
 
ValueCountFrequency (%) 
0.5721< 0.1%
 
0.032< 0.1%
 
0.0151< 0.1%
 
0.0121< 0.1%
 
0.0113< 0.1%